Grammar Specs

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UNL-NL grammars are sets of rules for translating UNL expressions into natural language (NL) sentences and NL sentences into UNL expressions. They are normally unidirectional, i.e., the UNL-ization grammar (NL-to-UNL) is different from the NL-ization grammar (UNL-to-NL), even though they share the same basic syntax.

Basic symbols

Basic symbols used in UNL grammar rules
Symbol	Definition	Example
^	not	^a = not a
{ \| }	or	{a\|b} = a or b
%	index for nodes, attributes and values	%x (see below)
#	index for sub-NLWs	#01 (see below)
=	attribute-value assignment	POS=NOU
!	rule trigger	!PLR
&	merge operator	%x&%y
?	dictionary lookup operator	?[a]
“ “	string	"went"
[ ]	natural language entry (headword)	[go]
[[ ]]	UW	[[to go(icl>to move)]]
( )	node	(a)
//	regular expression	/a{2,3}/ = aa,aaa

The differences between "", [] and [[]]: Double quotes are always used to represent strings: "a" will match only the string "a"; Simple square brackets are always used to represent natural language entries (headwords) in the dictionary: [a] will match the node associated to the entry [a] retrieved from the dictionary, no matter its current realization, which may be affected by other rules (the original [a] may have been replaced, for instance, by "b", but will still be indexed to the entry [a]); Double square brackets are always used to represent UWs: [[a]] will match the node associated to the UW [[a]]

Predefined values (assigned by default): SCOPE - Scope; SHEAD - Sentence head (the beginning of a sentence); STAIL - Sentence tail (the end of a sentence); CHEAD - Scope head (the beginning of a scope); CTAIL - Scope tail (the end of a scope); TEMP - Temporary entry (entry not found in the dictionary); DIGIT - Any sequence of digits (i.e.: 0,1,2,3,4,5,6,7,8,9)

Basic concepts

Nodes

A node is the most elementary unit in the grammar. It is the result of the tokenization process, and corresponds to the notion of "lexical item", to be represented by dictionary entries. At the surface level, a natural language sentence is considered a list of nodes, and a UNL graph a set of relations between nodes. Any node is a vector (one-dimensional array) containing the following necessary elements:

a string, to be represented between "quotes", which expresses the actual state of the node;
a headword, to be represented between [square brackets], which expresses the original value of the node in the dictionary;
a UW, to be represented between [[double square brackets]], which expresses the UW value of the node;
a feature or set of features, which express the features of the node;
an index, preceded by the symbol %, which is used to reference the node;

Examples of nodes are

("ing") (a node making reference only to its actual string value)
([book]) (a node making reference only to its headword,i.e., its original state in the dictionary)
([[book(icl>document)]]) (a node making reference only to its UW value)
(NUM) (a node making reference only to one of its features)
(POS=NOU) (a node making reference only to one of its features in the attribute-value pair format)
(%x) (a node making reference only to its unique index)
("string",[headword],[[UW]],feature1,feature2,...,attribute1=value1,attribute2=value2,...,%x) (complete node)

Properties of nodes

Nodes are enclosed between (parentheses): ("a") is a node; "a" is not a note
The elements of a node are separated by comma: ("a",[a],[[a]],A,B,A=C,%a)
The order of elements inside a node is not relevant.: ("a",[a],[[a]],A,B,A=C,%a) is the same as ([[a]],B,A,"a",[a],A=C,%a)
Nodes may have one single string, headword, UW and index, but may have as many features as necessary: ~~("a","b")~~ (a node may not contain more than one string); ~~([a],[b])~~ (a node may not contain more than one headword); ~~([[a]],[[b]])~~ (a node may not contain more than one UW); ~~(%a,%b)~~ (a node may not contain more than one index); (A,B,C,D,...,Z) (a node may contain as many features as necessary)
A node may be referred by any of its elements: ("a") refers to all nodes where actual string = "a"; ([a]) refers to all nodes where headword = [a]; ([[a]]) refers to all nodes where UW = [[a]]; (A) refers to all nodes having the feature A; ("a",[a],[[a]],A) refers to all nodes having the feature A where string = "a" and headword = [a] and UW = [[a]]
Nodes are automatically indexed according to a position-based system if no explicit index is provided (see Index): ("a")("b") is actually ("a",%01)("b",%02)
Regular expressions may be used to make reference to any element of the node, except the index: ("/a{2,3}/") refers to all nodes where string is a sequence of 2 to 3 characters "a"; ([/a{2,3}/]) refers to all nodes where headword is a sequence of 2 to 3 characters "a"; ([[/a{2,3}/]]) refers to all nodes where UW is a sequence of 2 to 3 characters "a"; (/a{2,3}/) refers to all nodes having a feature that is a sequence of 2 to 3 characters "a"
Nodes may contain disjoint features enclosed between {braces} and separated by comma: ({A|B}) refers to all nodes having the feature A OR B
Node features may be expressed as simple attributes, or attribute-value pairs: (MCL) - feature as an attribute: refers to all nodes having the feature MCL; (GEN=MCL) - feature as an attribute-value pair, which is the same as (GEN,MCL): refers to all nodes having the features GEN and MCL.

Attribute-value pairs may be used to create co-reference between different nodes (as in agreement):

(%x,GEN)(%y,GEN=%x) - the value of the attribute GEN of the node %x is the same of the attribute GEN of the node %y (see Index)

Relations

In order to form a natural language sentence or a UNL graph, nodes are inter-related by relations. In the UNL framework, there can be three different types of relations:

the linear relation L expresses the surface structure of natural language sentences
syntactic relations express the deep (tree) structure of natural language sentences
semantic relations express the structure of UNL graphs

Properties of relations

The linear relation is always binary and is represented in two possible formats

L(%x;%y), where L is the invariant name of the linear relation, and %x and %y are nodes; or
(%x)(%y)

Syntactic relations are not predefined, although we have been using a set of binary relations based on the X-bar theory.
Semantic relations constitute a predefined and closed set that can be found here.
Syntactic and semantic relations are represented in the same way

rel(%x;%y), where "rel" is the name of the relation, %x is the source node, and %y is the target node

Arguments of linear, syntactic and semantic relations are not commutative.

The order of the elements in a relation affects the result:

(%x)(%y) is different from (%y)(%x)

relation(%x;%y) is different from relation(%y;%x)

Linear and semantic relations are always binary; syntactic relations may be n-ary: L(%x;%y) - linear relation; agt(%x;%y) - semantic relation; VH(%x) - unary syntactic relation; VC(%x;%y) - binary syntactic relation; XX(%x;%y;%z) - possible ternary syntactic relation
Inside each relation, nodes are isolated by semicolon (;).: VC(%x;%y); ~~VC(%x,%y)~~
Inside each relation, nodes may be referenced by any of its elements, isolated by comma (,): ("a")([b]) - linear relation between a node where string = "a" and another node where headword = [b]; L([[c]];D) - linear relation between a node where UW = [[c]] and another node having the feature D; VC(%a;%b) - syntactic relation between a node where index = %a and another node where index = %b; agt("a",[a],[[a]],A;"b",[b],[[b]],B) - semantic relation between a node having the feature A where string = "a" AND headword "a" AND UW = [[a]] AND another node having the feature B where string = "b" AND headword = [b] AND UW = [[b]]
Relations may be conjoined through juxtaposition: ("a")("b")("c") - two linear relations: one between ("a") and ("b") AND other between ("b") and ("c"); agt(%x;%y)obj(%x;%z) - two semantic relations: one between (%x) and (%y) AND other between (%x) and (%z); ~~VC([a];[b]),VC([a];[c])~~ - conjoined relations must not be isolated by comma
Relations may be disjoined through {braces}: {("a")|("b")}("c") - either ("a")("c") or ("b")("c"); {agt(%x;%y)|exp(%x;%y)}obj(%x;%z) - either agt(%x;%y)obj(%x;%z) or exp(%x;%y)obj(%x;%z)
Syntactic and semantic relations may be replaced by regular expressions: /.{2,3}/(%x;%y) - any relation made of two or three characters between %x and %y

Hyper-nodes

Nodes may contain one or more relations. In this case, they are said to be "hyper-nodes", and represent scopes or sub-graphs. As any node, hyper-nodes contain a string, a headword, a UW, an index and features, of which the internal relations are a special type. Examples of hyper-nodes are the following:

(("a")("b")) - a hyper-node containing a linear relation between the nodes ("a") and ("b")
(VC(%x;%y)VA(%x;%z)) - a hyper-node containing two syntactic relations: VC(%x;%y)AND VA(%x;%z)
(agt([a];[b])obj([a];[c])) - a hyper-node containing two semantic relations: agt([a];[b]) AND obj([a];[c])
(([kick],V)([the],D)([bucket],N),V,NTST) - a hyper-node having the features N and NTST and containing two linear relations: one between the nodes ([kick],V) and ([the],D), and other between ([the],D) and [bucket],N)
(([kick],V)([the],D)([bucket],N),"kick the bucket",[[die]],V,NTST) - the same as before, except for the fact that the hyper-node has string = "kick the bucket" and UW = [[die]]

Hyper-nodes may also contain internal hyper-nodes:

((("a")("b"))("c")) - a hyper-node containing a linear relation between the hyper-node (("a")("b")) and the node ("c")

Properties of hyper-nodes

As any node, hyper-nodes are expressed between (parentheses): (("a")("b"))
As any node, hyper-nodes may have one single string, one single headword and one single UW, but may have as many features and internal relations as necessary: (([kick],V)([the],D)([bucket],N),"kick the bucket",[kick the bucket],[[die]],V,NTST)
As any node, hyper-nodes may be referenced by any of its elements, including internal relations: (([kick],V)) - refers to any hyper-node containing the node ([kick],V); (([the],D)([bucket],N)) - refers to any hyper-node containing a linear relation between ([the],D) AND ([bucket],N); (([kick],D),([bucket],N)) - refers to any hyper-node containing the nodes ([kick],V) AND ([bucket],N)
When a hyper-node is deleted, all its internal relations are deleted as well: (([kick],V)([the],D)([bucket],N)):=; (the hyper-node is deleted, as well as the relations ([kick],V)([the],D) AND ([the],D)([bucket],N))

Hyper-relations

Relations may have relations as arguments. In this case, they are said to be "hyper-relations". Examples of hyper-relations are the following:

XP(XB(%a;%b);%c) - a syntactic relation XP between the syntactic relation XB(%a;%b) and the node %c
and(agt([a];[b]);agt([a];[c])) - a semantic relation "and" between the semantic relations agt([a];[b]) AND agt([a];[c])

Properties of hyper-relations

A hyper-relation may have one single relation as each argument

XP(XB(%a;%b);%c) - the source argument of the hyper-relation XP is a relation
XP(%a;XB(%b;%c)) - the target argument of the hyper-relation XP is a relation
XP(VC(%a;%b);VA(%a;%c)) - the source and the target argument of the hyper-relation XP are relations
~~XP(VC(%a;%b)VA(%a;%c);VS(%a;%d))~~ - a hyper-relation may not have more than one relation as one single argument (in this case, the hyper-relation XP contained two relations as the source argument)

Relations do not have strings, UWs, headwords or any features

~~XP(XB(%a;%b),"ab",[ab],[[ab]],A,B;%c)~~ (the relation XB(%a;%b) may not have strings, UWs, headwords or any features)

Types of rules

In the UNL Grammar there are two basic types of rules:

Transformation rules: Used to generate natural language sentences out of UNL graphs and vice-versa.
Disambiguation rules: Used to improve the performance of transformation rules by constraining their applicability.

The Transformation Rules follow the very general formalism

α:=β;

where the left side α is a condition statement, and the right side β is an action to be performed over α.

The Disambiguation Rules, which were directly inspired by the UNL Centre's former co-occurrence dictionary and knowledge base, follows a slightly different formalism:

α=P;

where the left side α is a statement and the right side P is an integer from 0 to 255 that indicates the probability of occurrence of α.

Transformation rules

Natural language sentences and UNL graphs are supposed to convey the same amount of information in different structures: whereas the former arranges data as an ordered list of words, the latter organizes it as a hypergraph. In that sense, translating from natural language into UNL and from UNL into natural language is ultimately a matter of transforming lists into networks and vice-versa.

The UNDLF generation and analysis tools assume that such transformation should be carried out progressively, i.e., through a transitional data structure: the tree, which could be used as an interface between lists and networks. Accordingly, the UNL Grammar states seven different types of rules (LL, TT, NN, LT, TL, TN, NT), as indicated below:

ANALYSIS (NL-UNL)
- LL - List Processing (list-to-list)
- LT - Surface-Structure Formation (list-to-tree)
- TT - Syntactic Processing (tree-to-tree)
- TN - Deep-Structure Formation (tree-to-network)
- NN - Semantic Processing (network-to-network)

GENERATION (UNL-NL)
- NN - Semantic Processing (network-to-network)
- NT - Deep-Structure Formation (network-to-tree)
- TT - Syntactic Processing (tree-to-tree)
- TL - Surface-Structure Formation (tree-to-list)
- LL - List Processing (list-to-list)

The NL original sentence is supposed to be preprocessed, by the LL rules, in order to become an ordered list. Next, the resulting list structure is parsed with the LT rules, so as to unveil its surface syntactic structure, which is already a tree. The tree structure is further processed by the TT rules in order to expose its inner organization, the deep syntactic structure, which is supposed to be more suitable to the semantic interpretation. Then, this deep syntactic structure is projected into a semantic network by the TN rules. The resultant semantic network is then post-edited by the NN rules in order to comply with UNL standards and generate the UNL Graph.

The reverse process is carried out during natural language generation. The UNL graph is preprocessed by the NN rules in order to become a more easily tractable semantic network. The resulting network structure is converted, by the NT rules, into a syntactic structure, which is still distant from the surface structure, as it is directly derived from the semantic arrangement. This deep syntactic structure is subsequently transformed into a surface syntactic structure by the TT rules. The surface syntactic structure undergoes many other changes according to the TL rules, which generate a NL-like list structure. This list structure is finally realized as a natural language sentence by the LL rules.

As sentences are complex structures that may contain nested or embedded phrases, both the analysis and the generation processes may be interleaved rather than pipelined. This means that the natural flow described above is only "normal" and not "necessary". During natural language generation, a LL rule may apply prior to a TT rule, or a NN rule may be applied after a TL rule. Rules are recursive and must be applied in the order defined in the grammar as long as their conditions are true, regardless of the state.

Types of Transformation Rules

List-to-List Rules

The list-to-list (LL) rules are used for processing lists, both in analysis and in generation. In analysis, these rules are used for pre-editing the natural language sentence and preparing the input to the syntactic module; in generation, they are used for post-editing the output of the syntactic module and generating the natural language sentence.

There are 5 different subtypes of LL rules:

LL rules
ACTION	RULE	DESCRIPTION
ADD	(%x):=(%x)(%y);	The node %y is added to the right of the node %x
ADD	(%x):=(%y)(%x);	The node %y is added to the left of the node %x
DELETE	(%x):=-(%x);	The node %x is deleted.
DELETE	(%x):=;	The node %x is deleted.
REPLACE	(%x):=(%y);	All the instances of the node %x will be replaced by the node %y
MERGE	(%x)(%y):=(%x&%y);	The nodes %x and %y will be merged

Where %x and %y are nodes.

Tree-to-Tree Rules

The tree-to-tree rules (TT) are used for processing trees, both in analysis and in generation. During analysis, these rules are used for revealing the deep structure out of the surface structure; in generation, they are used for transforming the deep into the surface syntactic structure.

Syntactic relations are n-ary: they can have as many arguments (nodes) as necessary.

There are 3 different subtypes of TT rules:

TT rules
ACTION	RULE	DESCRIPTION
ADD RELATION	SYN1(%x;%y):=+SYN2(%w;%z);	The relation SYN2 between the nodes %w and %z will be added to the graph containing the relation SYN1 between the nodes %x and %y
DELETE RELATION	SYN(%x;%y):=-SYN(%x;%y);	The relation SYN between the nodes %x and %y will be deleted (the nodes %x and %y will not be deleted)
DELETE RELATION	SYN(%x;%y)=;
REPLACE RELATION	SYN1(%x;%y):=SYN2(%w;%z);	The relation SYN1 between the nodes %x and %y will be replaced by the relation SYN2 between the nodes %w and %z

Where SYN is a syntactic relation, and %x, %y, %z and %w are nodes.

As syntactic relations are n-ary, the REPLACE RELATION may also be used to ADD or DELETE nodes.

Special types of TT replace relations
ACTION	RULE	DESCRIPTION
ADD NODE	SYN(%x;%y):=SYN(%x;%y;%z);	The binary relation SYN between the nodes %x and %y is replaced by a ternary relation SYN between the nodes %x, %y and %z
DELETE NODE	SYN(%x;%y):=SYN(%y);	The binary relation SYN between the nodes %x and %y is replaced by a unary relation SYN with the node %y

Where SYN is a syntactic relation, and %x, %y and %z are nodes.

Network-to-Network Rules

The network-to-network rules (NN) are used for processing networks, both in analysis and in generation. During analysis, these rules are used for post-editing the semantic network structure derived from the syntactic module in order to generate the UNL graph; in generation, they are used for pre-editing the UNL graph, transforming it into a semantic network that would be more appropriate for sentence generation.

There are 3 different subtypes of NN rules:

NN rules
ACTION	RULE	DESCRIPTION
ADD RELATION	SEM1(%x;%y):=+SEM2(%w;%z);	The relation SEM2 between the nodes %w and %z will be added to the graph containing the relation SEM1 between the nodes %x and %y
DELETE RELATION	SEM(%x;%y):=-SEM(%x;%y);	The relation SEM between the nodes %x and %y will be deleted (the nodes %x and %y will not be deleted)
DELETE RELATION	SEM(%x;%y)=;
REPLACE RELATION	SEM1(%x;%y):=SEM2(%w;%z);	The relation SEM1 between the nodes %x and %y will be replaced by the relation SEM2 between the nodes %w and %z

Where SEM is any of the existing UNL relations, and %x, %y, %z and %w are nodes.

List-to-Tree Rules

The list-to-tree (LT) rules are used to parse the list structure into a tree structure.
There are 2 different subtypes of LT rules:

LT rule
ACTION	RULE	DESCRIPTION
ADD	(%x)(%y):=+SYN(%x;%y);	The relation SYN is created between the nodes %x and %y if there is a linear relation between them (the linear relation is not deleted)
REPLACE	(%x)(%y):=SYN(%x;%y);	The linear relation between %x and %y is replaced by the relation SYN between the same nodes (i.e., the linear relation is deleted)

Where SYN is a syntactic relation, and %x and %y are nodes.

Tree-to-List Rules

The tree-to-list (TL) rules are used to linearize the tree structure into a list structure. There is one single type of TL rule:

There is a single type of TL rule:

TL rule
ACTION	RULE	DESCRIPTION
REPLACE	SYN(%x;%y):=(%x)(%y);	The relation SYN between %x and %y is replaced by a linear relation between %x and %y

Where SYN is a syntactic relation and %x and %y are nodes.

Tree-to-Network Rules

The tree-to-network (TN) rules derive a semantic network out of a syntactic tree.

There are 2 types of TN rules:

TN rule
ACTION	RULE	DESCRIPTION
ADD	SYN(%x;%y):=+SEM(%w;%x);	The semantic relation SEM between the nodes %w and %x is created if there is a syntactic relation SYN between the nodes %x and %y
REPLACE	SYN(%x;%y):=SEM(%x;%y);	The syntactic relation SYN between the nodes %x and %y is replaced by the semantic relation SEM between the same nodes.

Where SYN is a syntactic relation, SEM is a semantic relation, and %x, %y, %w and %z are nodes.

Network-to-Tree Rules

The network-to-tree (NT) rules reorganizes the network structure as a deep tree structure.

There are two types of TN rules:

NT rule
ACTION	RULE	DESCRIPTION
ADD	SEM(%x;%y):=+SYN(%w;%x);	The syntactic relation SYN between the nodes %w and %x is created if there is a semantic relation SEM between the nodes %x and %y
REPLACE	SEM(%x;%y):=SYM(%x;%y);	The semantic relation SEM between the nodes %x and %y is replaced by the syntactic relation SYN between the same nodes.

Where SYN is a syntactic relation, SEM is a semantic relation, and %x, %y, %w and %z are nodes.

Transformations over nodes

Altering nodes

Nodes are altered by the use of the operators + (add) and - (delete). The operator + may be omitted.

(%x,A):=(%x,+B); (add the feature B to %x)
(%x,A):=(%x,B); (the same as above: add the feature B to %x)
(%x,A):=(%x,-A); (delete the feature A from %x)

"strings", [headwords] and [[UWs]] are considered to be features (but a single node may have only one of each)

(%x,A):=(%x,"a"); (replace the existing string in %x, if any, by "a")
(%x,[A]):=(%x,[A]); (replace the existing headword in %x, if any, by [A])
(%x,[[A]]):=(%x,[[A]]); (replace the existing UW in %x, if any, by [[A]])

Example:

("a",[a],[[a]],A,C,%x):=("b",[b],[[b]],-A,+B,%x); (the original node ("a",[a],[[a]],A,C) becomes ("b",[b],[[b]],B,C). Note that the feature C is preserved, because it was not affected by the rule);

Deleting nodes

In LL and LT rules, nodes are deleted if they are not repeated (co-indexed) in the right side:

(%x)(%y):=(%x); (the node %y will be deleted)

In other rules, nodes are deleted if they are not repeated (co-indexed) in the right side and are not part of any other relation:

rel(%x;%y):=rel(%x); (the node %y will be deleted if, and only if, it is not part of any other relation)

Creating nodes

Nodes are created through the use of new indexes in the right side:

("a",%x)("b",%y):=(%x)(%y)("c",%z); (the node %z will be created)
("a",%x)("b",%y):=(%x)("c",%z); (the node %z will be created, and %b will be deleted)

Duplicating (cloning) nodes

Nodes may be duplicated by repeating indexes on the right side along with the command #CLONE:

("a",%x)("b",%y):=(%x)(%y)(%x,#CLONE)(%y,#CLONE)(%y,#CLONE)(%x,#CLONE);

("a")("b") becomes ("a")("b")("a")("b")("b")("a")
In order to avoid infinite recursion, it is important to alter conditions on the left side.
In order to avoid impossible graphs (a node cannot be a neighbor of itself) and assign different features to the different instances of the repeated nodes, the command #CLONE must be used.

Merging nodes (&)

Two or more nodes may be merged by the command &:

(%x)(%y)(%z):=(%x&%y&%z);

In the example above("a")("b")("c") becomes ("abc")

Merge operations concatenate headwords and UWs, and join features

("hw1",[[uw1]],F1,%x)("hw2",[[uw2]],F2,%y)("hw3",[[uw3]],F3,%z):=(%x&%y&%z);
The resulting node is ("hw1hw2hw3",[[uw1uw2uw3]],F1,F2,F3)

Compare the difference

(%x)(%y):=(%z); (the nodes %x and %y are replaced by %z, and their features are lost unless explicitly included in %z)
(%x)(%y):=(%x&%z); (the nodes %z and %y are merged)

Splitting nodes (retokenization)

Temporary nodes (i.e., nodes having the feature TEMP) may be split, but the feature TEMP may be assigned to any node.
See Retokenization

Transformations over hyper-nodes

Altering hyper-nodes

Hyper-nodes, as nodes, have features, which may be altered by the use of the operators + (add) and - (delete). Changes in the hyper-node do not affect the internal nodes and relations. The operator + may be omitted.

(REL(%x;%y),%z):=(%z,+B); (add the feature B to the hyper-node %z; the internal nodes %x and %y are not affected)
(REL(%x;%y),%z):=(%z,+B); (the same as above: add the feature B to %x)
(REL(%x;%y),%z,A):=(%z,-A);(delete the feature A from the hyper-node %z; the internal nodes %x and %y are not affected)

Deleting hyper-nodes

In LL and LT rules, hyper-nodes are deleted if they are not repeated (co-indexed) in the right side. In this case, all the inner nodes are deleted as well:

(REL(%x;%y),%z):=; (the hyper-node %z will be deleted, and all its internal nodes and relations as well)

In order to preserve the internal nodes, see Extarcting nodes out of hyper-nodes below

Creating hyper-nodes

Hyper-nodes are created through the encapsulation of existing nodes

(%x):=((%x),%y); (the hyper-node %y is created, with the node %x there inside)
REL(%x;%y):=(REL(%x;%y),%z); (the hyper-node %z is created, with the relation REL between the nodes %x and %y inside)
(%x)(%y):=((%x)(%y),%z); (the hyper-node %z is created, with the linear relation between the nodes %x and %y there inside)

Attention: relations and nodes must be repeated in the right side or they will be deleted

(%x):=(%y); (the node %x will be simply replaced by %y; no hyper-node will be created)
REL(%x;%y):=(%z); (the relation REL between the nodes %x and %y will be replaced by the node %z; no hyper-node will be created)

Extracting nodes out of hyper-nodes

Nodes may be extracted from hyper-nodes by removing the hyper-node parentheses. In this case, the hyper-node is deleted (along with its features), but the internal nodes and relations are preserved, if repeated on the right side.

((%x),%y):=(%x); (the hyper-node %y is deleted, but its internal node %x is preserved; in case %y have nodes other than %x, these nodes will be deleted as well, because they are not repeated in the right side)
(REL(%x;%y),%z):=REL(%x;%y); (the hyper-node %z is deleted, but its internal relation REL(%x;%y) is preserved; in case %z have relations other than REL(%x;%y), and nodes other than %x and %y, these will be deleted as well, because they are not repeated in the right side.

Transformations over relations and hyper-relations

Relations and hyper-relations do not have features, and are replaced, created and deleted by NN, TT, NT, TN, TL and LT rules:

REL1(%x;%y):=REL2(%x;%y); (replacement)
REL(%x;%y):=; (deletion)
REL1(%x;%y):=+REL2(%w;%z); (creation)

Creating hyper-relations

Hyper-relations are created through encapsulating relations:

REL1(%x;%y)REL2(%x;%z):=REL1(REL2(%x;%z);%y); (the relation REL1 between %x and %y becomes a hyper-relation between the relation REL2(%x;%z) and the node %y.)

Transforming hyper-relations into simple relations

Hyper-relations are transformed into simple relations by removing their internal relations:

REL1(REL2(%x;%z);%y):=REL1(%x;%y)REL2(%x;%z); (the hyper-relation REL1 between the relation REL2(%x;%z) and the node %y is transformed into a simple relation between the nodes %x and %y; the relatin REL2(%x;%z) is not affected.)

Special types of transformation rules

Retrieving entries in the dictionary (?)

Dictionary entries may be accessed from transformation rules by the command "?"

(?[headword]) retrieves the first entry in the dictionary with the headword "headword"
(?[[uw]]) retrieves the first entry in the dictionary with the UW "uw"
(?[headword],?[[uw]],?feature) retrieves the first entry in the dictionary with the headword "headword", the UW "uw" and the feature "feature"

Regular expressions, variables and disjunction may also be used in dictionary search

(?[/abcd./]) retrieves the first entry in the dictionary whose headword has 5 characters and begins with "abcd" (this works only in natural language generation)
(?[[/abcd./]]) retrieves the first entry in the dictionary whose UW has 5 characters and begins with "abcd" (this works only in natural language analysis)

Obligatory parameters: Due to the indexation algorithm, the headword is obligatory in IAN and the UW is obligatory in EUGENE:

(?[headword]) will work only in IAN
(?[[uw]]) will work only in EUGENE
(?feature) will not work in IAN or EUGENE

Variables: In order to avoid repetition, dictionary look-up may use the values of indexed nodes in the left side

(?[%x]) retrieves the first entry in the dictionary with the same headword of the node %x
(?[[%x]]) retrieves the first entry in the dictionary with the same UW of the node %x
(?[%x],ATT=%x) retrieves the first entry in the dictionarz with the same headword of the node %x and whose attribute ATT has the same value of the attribute ATT of the node %x

Example

Dictionary search is used mainly in natural language generation

(N,NUM,GEN,@def,%noun):=(?[[]],?ART,?DEF,?NUM=%noun,?GEN=%noun)(%noun,-@def);

In case of node %noun with the features noun (N), number (NUM) and gender (GEN), and with the attribute @def (definite), search the first entry in the dictionary associated with the UW "" (empty UW) with the features ART and DEF, and whose attributes NUM and GEN have the same values of the ones of the node %noun, and insert it in front of the noun. Remove @def from the noun in order to avoid an infinite loop.

Triggering rules (!)

Inflectional rules are triggered in the grammar by the command "!"<ATTRIBUTE>. Given the dictionary entry:

[foot] "foot" (POS=NOU, NUM(PLR:="oo":"ee")) <eng,0,0>;

The rule NUM(PLR:="oo":"ee") is triggered by !NUM
For instance:

(NUM=PLR,^inflected):=(!NUM,+inflected); or
(PLR,^inflected):=(!NUM,+inflected); or
(NUM,^inflected):=(!NUM,+inflected);

In the first case (NUM=PLR), the system verifies if the attribute "NUM" is set and if it has the value "PLR". In the second and in the third case, the system simply verifies if the word has any feature (attribute or value) equal to "PLR" or "NUM".
It's important to stress that, as the features of the dictionary are defined by the user, there is no way of pre-assigning attribute-value pairs. In that sense, it's not possible to infer that "PLR" will be a value of the attribute "NUM" except through an assignment of the form "NUM=PLR" (i.e., given only "PLR" or "NUM", is not possible to state "NUM=PLR").

General properties of transformation rules

PRIORITY

Rules are applied serially, according to the order defined in the grammar. The first rule will be the first to be applied, the second will be the second, and so on. In case of the same rule being applicable more than once, rules are applied from left to right (in case of lists) and top-down (in case of graphs).

For instance:

List structure

INPUT = [a][ ][beautiful][ ][book]

GRAMMAR =

RULE#1: ([ ]):=; (delete the blank space)

RULE#2: ([beautiful])([ ])([book]):=([book])([beautiful]); (replace "beautiful+blank+book" by "book+beautiful")

RESULT:

INITIAL STATE: [a][ ][beautiful][ ][book]

STATE#1: [a][beautiful][ ][book] (the RULE#1 is the first applicable rule to appear in the grammar and, therefore, is the first one to be applied, and it will apply to the leftmost blank)

STATE#2: [a][beautiful][book] (the RULE#1 applies a second time, because there is a second blank space in the input)

FINAL STATE: [a][beautiful][book] (the RULE#2 never applies, because its condition is no longer true after the second application of RULE#1)

Graph structure

INPUT = mod(book,beautiful)mod(book,new)

GRAMMAR =

RULE#1: mod(%x;%y):=NA(%x;%y); (replace the mod relation between the nodes %x and %y by a NA relation between the same nodes)

RESULT:

INITIAL STATE: mod(book,beautiful)mod(book,new)

STATE#1: NA(book,beautiful)mod(book,new) (the RULE#1 is the first applicable rule to appear in the grammar and, therefore, is the first one to be applied, and it will apply to the topmost relation, i.e., the first one to appear in the graph)

STATE#2: NA(book,beautiful)NA(book,new) (the RULE#1 applies a second time, because there is a second mod relation to be replaced)

FINAL STATE: NA(book,beautiful)NA(book,new)

RECURSIVENESS: Rules are applied recursively as long as their conditions are true. Because of that, special attention should be paid to ADD rules:

~~(%x,A):=(%x,+B);~~ (creates an infinite loop, because the feature B will be added infinitely to the node %x)

In order to avoid the endless repetition, the condition side must be changed to (%x,A,^B):=(%x,+B); (the rule applies only once)

~~REL1(%x;%y):=+REL2(%x;%z);~~ (creates an infinite loop, because the REL2 will be added infinitely to the graph)

In order to avoid the endless repetition, the condition side must be changed to REL1(%x;%y)^REL(%x;%z):=+REL2(%x;%z); OR REL1(%x,^BREAK;%y):=+REL2(%x,+BREAK;%z); (the rule applies only once)

COMPREHENSIVENESS: Grammars are applied comprehensively as long as there is at least one applicable rule.

CONSERVATION

Rules affect only the information clearly specified. No relation, node or feature is deleted unless explicitly informed.

For instance, in the examples below, the source node of the “agt” relation preserves, in all cases, the value “a”. The only change concerns the feature “c”, which is added to the source node of the “agt” in the first two cases; and the feature “b”, which is deleted from the target node in the third case.

agt(a;b):=agt(c;);

agt(a;b):=agt(+c;);

agt(a;b):=agt(;-b);

In any case, the ADD and DELETE rules (i.e., when the right side starts with “+” or “-“) preserve the items in the left side, except for the explicitly deleted ones:

INPUT: agt(%x;%y) obj(%x;%z) tim(%x;%w)

RULE: agt(%x;%y) ^mod(%x;%k):=+mod(%x;%k);

OUTPUT: agt(%x;%y) obj(%x;%z) tim(%x;%w) mod(%x;%k)

or

INPUT: agt(%x;%y) obj(%x;%z) tim(%x;%w)

RULE: agt(%x;%y):=-agt(%x;%y);

OUTPUT: obj(%x;%z) tim(%x;%w)

SCOPE

LL and LT rules apply over nodes, whereas NN, TT, NT, TN and TL rules apply over relations.

Nodes may be deleted only through LL and LT rules (i.e., when appearing in the left side of rules).

(A):=; (the node containing the feature "A" is deleted)

(%A,A):=-(%A); (the node containing the feature "A" is deleted - the same as above)

(%A,A)(%B,B):=(%A); (the node containing the feature "B" is deleted because not present in the right side - see indexes)

(%A,A)(%B,B)(%C,C):=REL(%A;%B); (the node containing the feature "C" is deleted, because not present in the right side - see indexes)

Nodes may not be deleted through NN, TT, NT, TN and TL rules (i.e., when not appearing in the left side of rules).

REL(%A,A;%B,B;%C,C):=(%A)(%B); (the relation between the nodes containing the features "A", "B" and "C" is replaced by a linear relation between the nodes containing the features "A" and "B". The node "C", however, is not deleted, even though absent from the right side - see indexes)

Relations may be deleted directly through NN, TT, NT, TN and TL rules, and indirectly through LL and LT rules (when their nodes are deleted).

REL(A;B):=; (The relation between the nodes containing the features "A" and "B" is deleted, but the nodes are preserved)

REL(A;B)REL(%C,C;%D,D):=REL(%C;%D); (The relation between the nodes containing the features "A" and "B" is deleted; its nodes and the relation between the nodes containing the features "C" and "D" are preserved)

(A):=; (The node containing the feature "A" is deleted, as well as all relations in which it figures as an argument)

INDEXATION: All instances of the same node must be co-indexed (or they will be considered different nodes). See indexes.

ACTION

Rules may add or delete values to the source and the target nodes, but only in the right side items:

agt(a;b):=agt(+c;);

agt(a;b):=agt(;-b);

CONJUNCTION

Both the left and the right side of the rule may have as many items as necessary, as exemplified below:

SEM(A;B)SEM(C;D)SEM(E;F):=SEM(G;H)SEM(I;J)SEM(K;L);

DISJUNCTION

The left side of the rules may bring disjuncts, but not the right side. Disjuncts must be represented between {braces} and must be separated by |.

{SEM(A;B)|SEM(C;D)}^SEM(E;F):=+SEM(E;F);

SEM(A;B){SEM(C;D)|SEM(E;F)}:=-SEM(A;B);

agt(VER,{V01|V02};NOU,^SNG}:=;

REGULAR EXPRESSIONS

The left side of the rules may bring [Perl Compatible Regular Expressions] between "/", as indicated below:

/(agt|obj|aoj)/(A,%a;B,%b):=VS(%a;%b);

The rule above applies in case of agt(A;B), obj(A;B) and aoj(A;B)

/[a-z]{2,3}/(A,%a;B,%b):=VS(%a;%b);

The rule above applies in case of any sequence of two or three alphabetic characters in the position of relation of A and B

agt(/(VER|NOU)/,%a;%b):=VS(%a;%b);

The rule above applies in case of VER and NOU as features of the first node of the relation "agt"

agt(POS=/(VER|NOU)/,%a;%b):=VS(%a;%b);

The rule above applies in case of VER and NOU as values of the attribute POS of the first node of the relation "agt"

CONCISION

In order for rules to be as small as possible, the source and the target nodes may be simple place-holders or indexes:

cob(;):=obj(;);

tim(%01;[[in]]),obj([[in]];%02):=tim(%01;%02);

tim(VER,%01;[[in]]),obj([[in]];NOU,%02):=tim(%01;%02);

tim(VER;in),obj(in;NOU):=tim(;%04);

In the DELETE rules, the right side may be omitted in case of deletion of the entire left side:

obj(PRE;):=;

READABILITY

There can be blank spaces between variables and symbols. Comments can be added after the “;”.

obj ( ; ) := ; this rule deletes every “obj” relation.

COMMUTATIVITY

Inside the same side of NN, NT, TT and TN rules, the order of the factors does not affect the result^[1]

SEM(A;B):=SEM(C;D)SEM(E;F); IS EQUIVALENT TO SEM(A;B):= SEM(E;F)SEM(C;D);

SYN(A;B):=SYN(C;D)SYN(E;F); IS EQUIVALENT TO SYN(A;B):= SYN(E;F)SYN(C;D);

The order of the factors affect the result in case list-processing rules (LL, LT and TL):

(A):=(B)(C); IS DIFFERENT FROM (A):=(C)(B);

SYN(A;B):=(C)(D); IS DIFFERENT FROM SYN(A;B):=(D)(C);

(C)(D):=SYN(A;B); IS DIFFERENT FROM (D)(C):=SYN(A;B);

Additionally, the order of the features inside a relation does not affect the end result, but the order of the nodes is non-commutative.

SEM( VER,TRA ; NOU,MCL ) IS THE SAME AS SEM( TRA,VER ; MCL,NOU )

But:

SEM( VER,TRA ; NOU,MCL) IS DIFFERENT FROM SEM( NOU,MCL ; VER,TRA )

DICTIONARY ATTRIBUTES

Dictionary attributes can be used as variables (see indexes).

SYN(%x,^NUM;%y,NUM):=SYN(NUM=%y;%x);

DICTIONARY RULES (see also Inflection rules inside dictionary entries)

Dictionary rules are triggered by "!"<ATTRIBUTE>:

Dictionary

[foot] "foot" (NOU, NUM(PLR:=”oo”:”ee”)) <eng,0,0>;

[city] "city" (NOU, NUM(PLR:=”y”>”ies”)) <eng,0,0>;

Grammar

(@pl, NUM):=(!NUM,-@pl);

Output

foot>feet

city>cities

NLW SPLITTING

Sub-NLWs in complex entries are referred by # (see indexes).

Dictionary

[[bring] [back]] "bring back" (VER,MTW,VA(01>02), #01(HEAD,VER), #02(ADJT,PP)) <eng,0,0>;

Grammar

VC(VER,MTW,VA(01>02),%head;NOU,%obj):=VB(VC(%head#01;%obj);%head#02);

Formal Syntax of Transformation Rules

<TRANSFORMATION RULE> ::= <NN RULE> | <NT RULE> | <TT RULE> | <TL RULE> | <LL RULE> | <LT RULE> | <TN RULE>
<NN RULE>             ::= (<SEM>)+ ":=" ( ("-"|"+")? <SEM> )* ";"
<TT RULE>             ::= (<SYN>)+ ":=" ( ("-"|"+")? <SYN> )* ";"
<LL RULE>             ::= ( "(" <NODE> ")" )+ ":=" ( ("-"|"+")? "(" <NODE> ")" )* ";"
<NT RULE>             ::= (<SEM>)+ ":=" ( <SYN> )+ ";"
<TN RULE>             ::= (<SYN>)+ ":=" ( <SEM> )+ ";"
<TL RULE>             ::= (<SYN>)+ ":=" ( "(" <NODE> ")" )+ ";"
<LT RULE>             ::= ( "(" <NODE> ")" )+ ":=" ( <SYN> )+ ";"
<SEM>                 ::= <TEXT> "(" <NODE> ";" <NODE> ")"
<SYN>                 ::= <TEXT> "(" <NODE> ";" <NODE> ")"
<NODE>                ::= ( (<DESCRIPTION>)( "," <DESCRIPTION> )* )?
<DESCRIPTION>         ::= <STRING> | <ENTRY> | <SUB-ENTRY> | <FEATURE> | <INDEX> | <RELATION>
<STRING>              ::= """<text>"""
<ENTRY>               ::= "["<entry>"]"
<SUB-ENTRY>           ::= <INDEX>"#"[01-99]
<FEATURE>             ::= <VALUE> | <ATTRIBUTE> | <ATTRIBUTE>"="<VALUE>
<INDEX>               ::= ( "%"([01-99]|[a-zA-Z_]+) )+
<RELATION>            ::= <SEM>|<SYN>
<VALUE>               ::= <TEXT>
<ATTRIBUTE>           ::= <TEXT>
<TEXT>                ::= any sequence of characters except whitespace | <REGULAR EXPRESSION>
<REGULAR EXPRESSION>  ::= "/"<PERL COMPATIBLE REGULAR EXPRESSIONS>"/"

Where:
"" = constant
+ = to be repeated one or more times
* = to be repeated zero or more times
? = to be repeated zero or one time
| = or
[x-y] = from x to y

Disambiguation Rules

Apart from Transformation Rules, the UNL Grammar also comprises Disambiguation Rules, which are optional and may be used to:

Prevent wrong lexical choices;
Provoke best matches;
Check the consistency of the graphs, trees and lists.

The formalism here presented is directly inspired by UNL Centre former co-occurrence dictionary and knowledge-base. The structure of the rule is as follows:

STATEMENT=P;

Where
STATEMENT is any network, tree or list relation; and
P, which can range from 0 (impossible) to 255 (necessary), is the probability of occurrence of the STATEMENT

There are three types of disambiguation rules:

Network disambiguation rules
Tree disambiguation rules
List disambiguation rules

Network Disambiguation Rules

Network disambiguation rules apply over the network structure of UNL graphs to constrain the application of Tree-to-Network (TN) and Network-to-Network (NN) Transformation Rules. They have the following format:

SEM(A;B)=P;

Where SEM is a semantic relation, A and B are nodes, and P is an integer (from 0 to 255).

Examples

agt(VER;ADJ)=0;: An adjective (ADJ) may not be an agent (agt) of a verb (VER).
agt(VER;NOU)=255;: Agents (agt) of verbs (VER) are always nouns (NOU).

Use

INPUT	TRANSFORMATION RULES	DISAMBIGUATION RULES	OUTPUT
SYN(A,B,C;D,E,F)	SYN(A;D)=agt(;); (higher priority) SYN(A;E)=aoj(;); (lower priority)	agt(A;F)=0;	aoj(A,B,C;D,E,F)

Tree Disambiguation Rules

Tree disambiguation rules apply over the intermediate tree structure to constrain the application of List-to-Tree (LT), Network-to-Tree (NT) and Tree-to-Tree (TT) Transformation Rules. They have the following format:

SYN(A;B)=P;

Where SYN is a syntactic relation, A and B are nodes, and P is an integer (from 0 to 255).

Examples

VS(VER;ADJ)=0;: An adjective (ADJ) may not be an specifier (VS) of a verb (VER).
NS(NOU;DET)=255;: Determiners (DET) are always specifiers (NS) of nouns (NOU).

Use

INPUT	TRANSFORMATION RULES	DISAMBIGUATION RULES	OUTPUT
(A,B,C)(D,E,F)	(A)(D)=X(A;D); (higher priority) (A)(E)=X(E;A); (lower priority)	X(F;A)=255;	X(D,E,F;A,B,C)
agt(A,B,C;D,E,F)	agt(A;D)=X(A;D); (higher priority) agt(A;E)=Y(A;E); (lower priority)	X(B;F)=0;	Y(A,B,C;D,E,F)

List Disambiguation Rules

List disambiguation rules apply over the natural language list structure to constrain the application of both Tree-to-List (TL) and List-to-List (LL) Transformation Rules. They are also used for word selection. They have the following format:

(A)(B)=P;

Where A and B are nodes, and P is an integer (from 0 to 255).

Examples

(ART)(BLK)(VER)=0;: An article (ART) may not precede a verb (VER).
(ART)(BLK)(NOU)=255;: Articles (ART) always precede nouns (NOU).

Use

Rule Disambiguation
INPUT	TRANSFORMATION RULES	DISAMBIGUATION RULES	OUTPUT
X(A,B,C;D,E,F)	X(A;D)=(A)(D); (higher priority) X(A;F)=(F)(A); (lower priority)	(B)(E)=0;	(D,E,F)(A,B,C)

Word Disambiguation
INPUT	DICTIONARY	DISAMBIGUATION RULES	OUTPUT
the book	[book] "22222" (POS=VER); (higher priority) [book] "11111" (POS=NOU); (lower priority)	(ART)(BLK)(VER)=0;	[book] "1111" (POS=NOU);

Formal Syntax of Disambiguation Rules

Disambiguation rules must comply with the following syntax

<DISAMBIGUATION RULE> ::= <NN RULE> | <TT RULE> | <LL RULE> 
<NN RULE>             ::= (<SEM>)+ "=" [0-255]";"
<TT RULE>             ::= (<SYN>)+ "=" [0-255]";"
<LL RULE>             ::= "(" <NODE> ")" ( "(" <NODE> ")" )+ "=" [0-255]";"
<SEM>                 ::= <TEXT> "(" <NODE> ";" <NODE> ")"
<SYN>                 ::= <TEXT> "(" <NODE> ";" <NODE> ")"
<NODE>                ::= ( (<DESCRIPTION>)( "," <DESCRIPTION> )* )?
<DESCRIPTION>         ::= <STRING> | <ENTRY> | <FEATURE> | <RELATION>
<STRING>              ::= """<text>"""
<ENTRY>               ::= "["<entry>"]"
<FEATURE>             ::= <VALUE> | <ATTRIBUTE> | <ATTRIBUTE>"="<VALUE>
<RELATION>            ::= <SEM>|<SYN>
<VALUE>               ::= <TEXT>
<ATTRIBUTE>           ::= <TEXT>
<TEXT>                ::= any sequence of characters except whitespace | <REGULAR EXPRESSION>
<REGULAR EXPRESSION>  ::= "/"<PERL COMPATIBLE REGULAR EXPRESSIONS>"/"

Indexes

Indexes (%) are used for co-indexing nodes, attributes and values inside and between the left and the right side of transformation rules.: X(%a;)Y(%a;) (the first node of X is also the first node of Y); X(%a;%b):=Y(%b;%a); (the first node of X becomes the second node of Y, and the second node of X becomes the first node of Y); X(%a;)Y(%a;):=Z(%a); (if the first node of X is the first node of Y then make it the single node of Z)

Any co-indexation is made by the use of indexes and not by the repetition of features. In that sense, X(A;)Y(A;) is different from X(%a;)Y(%a;). In the former case, the first node of X is not necessarily the first node of Y, they only share the same feature A; in the latter case, the first node of X is necessarily the first node of Y.

Indexes are made of any sequence of alphanumeric characters and underscore: %index; %a; %first_index; %a1; ~~%first index~~ (no blank spaces are allowed)

%01 (numbers are used for default indexation and must be avoided - see below)

Default indexation

If omitted, indexes are assigned by default, according to the following rules:

Default indexes are assigned from left to right in each side of the rule according to the position of the nodes:

X(A;B)Y(C;D) is the same as X(%01,A;%02,B)Y(%03,C;%04,D)

Default indexation is done only for non-indexed nodes (i.e., user-defined indexes prevail over indexes assigned by default):

X(A,%A;B)Y(C,%C;D) is the same as X(A,%A;B,%02)Y(C,%C;%04,D)

(Notice that the user-defined indexes %A and %C are preserved and not replaced by default indexes)

In default indexation, left-side nodes are automatically co-indexed with right-side nodes if and only if their position and number are the same:

X(A;B):=Y(C;D); is the same as X(%01,A;%02,B):=Y(%01,C;%02,D);

X(A;B):=Y(C;D;E); is the same as X(%01,A;%02,B):=Y(%03,C;%04,D;%05,E);

(there is no co-indexation between the left and the right side in the latter case, because the number of the nodes is not the same)

Default indexes are also assigned to hyper-nodes and sub-nodes

(((A))):=(((B))); is the same as (%01(%01%01(%01%01%01,A))):=(%01(%01%01(%01%01%01,B)));

In default indexation, sub-nodes are informed by the syntax <PARENT NODE><CHILD NODE>, where <PARENT NODE> may be, itself, a sub-node:

X(Y(A;B);C) is the same as X(%01,Y(%01%01,A;%01%02,B);%02)

%01 = Y(A;B), %02 = C, %01%01 = A, %01%02 = B

X(Y(Z(A;B);C);D) is the same as X(%01,Y(%01%01,Z(%01%01%01,A;%01%01%02,B);%01%02,C);%02,D)

%01 = Y(Z(A;B);C), %02 = D, %01%01 = Z(A;B), %01%02 = C, %01%01%01 = A, %01%01%02 = B

Non-indexed nodes in the right side means ADDITION, whereas left-side nodes that are not referred to in the right side means DELETION

X(%a;%b):=Y(%a;X;%b); is the same as X(%a;%b):=Y(%a;%02,X,;%b); (it means that a new node with the feature X will be created for the relation Y)

X(%a;%b;%c):=Y(%a;%c); (it means that the second node of X will be deleted from the relation Y)

Indexes may also be used to transfer attribute values expressed in the format ATTRIBUTE=VALUE

X(A,%a,ATT1=VAL1;B,%b):=X(%a;%b,ATT1=%a); (the value "VAL1" of "ATT1" of %a is copied to the node %b)

Special indexes (#) are used to make reference to the internal structure of the field <NLW> in the dictionary

(X)(Y):=(X,#02)(Y)(X,#01);

The rule above is used for complex dictionary entries such as:

[[A][B]] "uw" (X, #01(ATT=AAA), #02(ATT=BBB)) <flg,fre,pri>;

It means that, given (X)(Y), the output should be (B)(Y)(A).

Examples of Rules

In the examples below:

L(A;B) is a linear (list) relation between A and B (i.e., L(A;B) = (A)(B))
REL(A;B) is a non-linear (tree or network) relation between A and B
%X is the index for a node
:X indicates that the following relation or node is inside the hyper-node X
A,B,C,D,B1,B2,B3 and B4 are features of the nodes %A,%B,%C,%D,%B1,%B2,%B3 and %B4, respectively.

LL RULES

INITIAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4)

LL#1: (B):=;: (Delete all nodes having the feature B, wherever they are); FINAL STATE: L(%A;%C) L(%C;%D); The whole hyper-node %B will be deleted, including all its nodes, no matter in which level.

LL#2: (B1):=;: (Delete all nodes having the feature B1, wherever they are); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B2;%B3) :B(%B4); Only the node (%B1) is deleted. The relation REL is also deleted, but the node %B4 is preserved as an isolated node inside the hyper-node %B.

LL#3: ((B1)):=;: (Delete any hyper-node that contains the node having the feature B1, wherever they are);; FINAL STATE: L(%A;%C) L(%C;%D); The whole hyper-node %B will be deleted, including all its nodes, no matter in which level.

LL#4: (B1):=(NEW);: (Add the feature “NEW” to all nodes having the feature B1); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4) (NO CHANGE IN THE NODE STRUCTURE); There is no indexes in the left and the right side, which have the same number of nodes. This means that they are automatically co-indexed. No node is deleted or replaced. The feature “NEW” is added to the the node %B1, because it contains the feature B1. This rule provokes a look, because the feature NEW will be added indefinitely to the node %B1. In order to avoid this, the condition should be set (B1,^NEW):=(NEW);

LL#5: (%x,B1):=(%y,NEW);: (Replace any node having the feature B1 by a new node having the feature NEW); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%NEW;%B2) L:B(%B2;%B3) REL:B(%NEW;%B4); The node %B1 is deleted and replaced by a new node %NEW. Notice that all instances of the node are replaced.

LL#6: ({(B1)|(B3)}):=;: (Delete any hyper-node that contains nodes having the features B1 or B3);; FINAL STATE: L(%A;%C) L(%C;%D); The whole hyper-node %B will be deleted, including all its nodes, no matter in which level.

LL#7: ((B1)(B2)):=;: (Delete any hyper-node that contains the relation L(B1;B2));; FINAL STATE: L(%A;%C) L(%C;%D); The whole hyper-node %B will be deleted, including all its nodes, no matter in which level.

LL#8: ((B1)(B3)):=;: (Delete any hyper-node that contains the relation L(B1;B3)); Nothing happens. The condition is not true in the case of the initial state indicated above.

LL#9: ((B1)):=(-feature);: (Remove the feature “feature” from any hyper-node containing a node with the feature B1); As the left and the right side do not have indexes, they are automatically co-indexed. The co-indexation, however, is valid only to the hyper-node level, because the right side does not contain any inner node. In that sense, the feature “feature” is not removed from the inner node, but from the hyper-node.

LL#10: ((B1)):=((-feature));: (Remove the feature “feature” from anynode having the feature B1 which is inside a hyper-node); The automatic indexation affects both levels: the hyper-node and the node, because they are equivalent. The rule is the same as (%x,(%y,B1)):=(%x,(%y,-feature));. The feature “feature” is now removed from the inner node and not from the hyper-node.

LL#11: ((%x,B1)):=((%y,NEW));: (Replace any node containing the feature B1 inside a hyper-node by a new node containing the feature 'NEW'); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%NEW;%B2) L:B(%B2;%B3) REL:B(%NEW;%B4); The same as (%x,B1):=(%y,NEW); but inside a hyper-node (i.e., the rule applies only to the nodes having the feature B1 which are inside some other node).

LL#12: ((B1)):=((E)(F));: (Replace any node containing the feature B1 by a linear relation between two new nodes containing the features E and F, respectively); FINAL STATE: : L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B2;%B3) REL:B(%HB;%B4) L:HB(%E;%F); The same as (%x,B1):=(%y,E)(%z,F); but inside a hyper-node (i.e., the rule applies only to the nodes having the feature B1 which are inside some other node). The linear relation between the nodes (%B1) and (%B2) disappear, because (%B1) is an argument of a non-linear relation REL(%B1;%B4) and should be replaced, therefore, by a hyper-node instead of a simple sequence of nodes (%E)(%F), since ~~REL((%E)(%F);(%B4))~~ is not possible. As a consequence, the nodes (%E) and (%F) are created inside the hyper-node %HB and may not hold any linear relation with %B2, because they are now in different scopes.

LL#13: ((B1)):=(((E)(F),-B1));: (Replace any node containing the feature B1 by a new node containing a linear relation between two new nodes containing the features E and F, respectively); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%HB;%B2) L:B(%B2;%B3) REL:B(%HB;%B4) L:HB(%E;%F); The same as (%x,(%a,B1)):=(%x,(%b,E)(%c,F)); but inside a hyper-node (i.e., the rule applies only to the nodes having the feature B1 which are inside some other node). Differently from the previous example, the node containg the feature B1 is replaced by a hyper-node and not by two other nodes of the same level. As the system is conservative, the feature B1 has to deleted in order to prevent the rule from applying eternally.

LL#14:((B1)):=((E),(F));: (Replace the node containing the feature B1 by two new nodes containing the features E and F, respectively); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%HB;%B2) L:B(%B2;%B3) REL:B(%HB;%B4) :HB(%E) :HB(%F); The nodes (E) and (F) no longer constitute a linear relation, and are added as isolated notes to the hyper-node. Because of that, (B1) has to be replaced, necessarily, by a hyper-node. This means that this rule will have exactly the same effect of the rule below.

LL#15:((B1)):=(((E),(F),-B1));: (Replace the node containing the feature B1 by two new nodes containing the features E and F, respectively); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%HB;%B2) L:B(%B2;%B3) REL:B(%HB;%B4) :HB(%E) :HB(%F); The nodes (E) and (F) no longer constitute a linear relation, and are added as isolated notes to the hyper-node. As the system is conservative, the feature B1 has to deleted in order to prevent the rule from applying eternally.

LL#16: (REL(%B1;%B4)):=(NEWREL(%B1;%B5));: (Replace the relation REL between the nodes %B1 and %B4 by a new relation NEWREL between the existing node %B1 and a new node %B5); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) NEWREL:B(%B1;%B5) :B(%B4); Nodes on both sides are automatically co-indexed, because their number is the same. Therefore, the relation on the left side is replaced by the relation on the right side in the same hyper-node. No node is deleted: notice that %B4 is still there. This is the same as REL(A;B):=REL(C;D);.

LL#17:(B1)(B2):=;: (The same as L(%B1;%B2):=; i.e., delete the linear relation between %B1 and %B2); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) :B(%B3) REL:B(%B1;%B4); The linear relation between (%B1) and (%B2) is deleted, but the nodes (%B1) and (%B2) are preserved if part of other non-linear relations.

LL#18:(B1)(B2):=(B5);: (The same as L(%B1;%B2):=(%B5); i.e., replace the linear relation between %B1 and %B2 by %B5); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B5;%B3) REL:B(%B1;%B4); The linear relation between (%B1) and (%B2) is replaced by %B5, but the nodes (%B1) and (%B2) are preserved if part of other non-linear relations.

LL#19:(%B1,B1)(B2):=(%B1);: (The same as L(%B1;%B2):=(%B1); i.e., replace the linear relation between %B1 and %B2 by %B1); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B3) REL:B(%B1;%B4); The linear relation between (%B1) and (%B2) is replaced by %B1, but the nodes (%B1) and (%B2) are preserved if part of other non-linear relations.

LL#20:(B1)(%B2,B2):=(%B2);: (The same as L(%B1;%B2):=(%B2); i.e., replace the linear relation between %B1 and %B2 by %B2); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B2;%B3) REL:B(%B1;%B4); The linear relation between (%B1) and (%B2) is replaced by %B2, but the nodes (%B1) and (%B2) are preserved if part of other non-linear relations.

LL#21:(%B1,B1)(%B2,B2):=(%B1,(%B2));: (replace the linear relation between %B1 and %B2 by the node %B1 with %B2 inside as an isolated node); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B3) REL:B(%B1;%B4) :B1(%B2); The linear relation between (%B1) and (%B2) is replaced by %B1, but the nodes (%B1) and (%B2) are preserved if part of other non-linear relations.

LL#22: (%D,D):=(%D,-D,+D1)(%D,-D,+D2);: (Duplicate the node having the feature D, wherever they are); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D1) L(%D1;%D2) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4); The whole hyper-node %D will be duplicated, including all its nodes, no matter in which level. Node duplication occurs only in LL rules. As the system is conservative, the feature D has to deleted in order to prevent the rule from applying eternally.

LT RULES

INITIAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4)

LT#1: (%B1,B1)(%B2,B2):=REL(%B1;%B2);: (Replace the relation L(%B1;%B2) by the relation REL(%B1;%B2)); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) REL:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4); No node is deleted, but there’s no longer a linear relation between %B1 and %B2. There’s still, however, a linear relation between %B2 and %B3 inside the hyper-node %B.

LT#2: (%B1,B1)(%B2,B2):=+REL(%B1;%B2);: (Add the relation REL(%B1;%B2) to the graph ); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4) REL(%B1;%B2); No node or relation is deleted. A new relation is created in the graph.

LT#3: (%B1,B1)(%B2,B2)(%B3,B3):=REL(%B1;%B2);: (Replace the relations L(%B1;%B2)L(%B2;%B3) by the relation REL(%B1;%B2)); FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) REL:B(%B1;%B2) REL:B(%B1;%B4); The node (%B3) is deleted because it is not present in the right side.

LT#4: (%B1,B1)(%B3,B3)(%B2,B2):=REL(%B1;%B2);: (Replace the relations L(%B1;%B3)L(%B3;%B2) by the relation REL(%B1;%B2)); Nothing happens. The condition is not true in this case.

LT#5: (%B1,B1):=REL(%B1;%B5); (Replace the node having the feature B1 by the relation REL(%B1;%B5)): FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B2;%B3) REL:B(%HB;%B4) REL:HB(%B1;%B5); There is no longer a linear relation between %B1 and %B2, because the node was replaced by a relation and, therefore, removed from the list structure.

LT#6: (%B1,B1):=+REL(%B1;%B5); (Add the relation REL(%B1;%B5) to the graph): FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4) REL(%B1;%B5); No node is replaced or deleted. A new relation is added to the graph.

LT#7: (REL(%B1,B1;%B4,B4)):=NEWREL(%B1;%B4); (Replace the hyper-node containing the relation REL by the relation NEWREL(%B1;%B5): FINAL STATE: L(%A;%C) L(%C;%D) NEWREL(%B1;%B4); The whole hyper-node %B will be replaced by the new relation. All its inner nodes not referred to in the right side will be deleted as well.

LT#8: (REL(%B1,B1;%B4,B4)):=+NEWREL(%B1;%B4); (Add the relation NEWREL(%B1;%B4) to the graph)</nowiki>: FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4) NEWREL(%B1;%B4); The hyper-node remains the same. The relation NEWREL(%B1;%B4) is added to its outer scope.

TL Rules

INITIAL STATE: L(%A;%B) L(%B;%C) REL:B(%B1;%B2) REL:B(%B1;%B3)

TL#1: REL(%B1;%B2)REL(%B1;%B3):=(%B1)(%B2);: (Replace the relation REL between the nodes %B1 and %B2 and the relation REL between the nodes %B1 and %B3 by a linear relation between %B1 and %B2); FINAL STATE: L(%A;%B) L(%B;%C) L:B(%B1;%B2) :B(%B3); The node %B3 is not deleted, but it does not have any other relation with any other node inside the hyper-node.

TT or NN Rules

INITIAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) REL:B(%B1;%B4)

TT#1:REL(%x;%y):=NEWREL(%x;%y): FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) NEWREL:B(%B1;%B4); The relation is changed, but the arguments %x and %y are preserved.

TT#2: REL(%x;%y):=REL(%w;%z): FINAL STATE: L(%A;%B) L(%B;%C) L(%C;%D) L:B(%B1;%B2) L:B(%B2;%B3) :B(%B4) REL(%w;%z); The relation between %x and %y is deleted, but the nodes are preserved. Noticed that %B4 became an isolated node, but it’s still there, because no node may be deleted by a NN rule.

INITIAL STATE : REL(%x;%y;%z)

TT#3:REL(%x;%y;%z):=REL(%x;%y);: FINAL STATE: REL(%x;%y) (%z); The node %z is not deleted.

Notes

↑ It is important to consider that the resulting order of relations may affect the application of other rules in some implementations. For instance, the rules "SEM(A;B):=SEM(C;D)SEM(E;F);" and "SEM(A;B):= SEM(E;F)SEM(C;D);" will provide the same result, but the relation "SEM(C;D)" may be listed before "SEM(E;F)" in the first case, and after it in the second case. This means that a general rule like SEM(;):=SYN(;);, which would be applicable to both generated relations, will be applied first to "SEM(C;D)" in the first case, and to "SEM(E;F)" in the second case.

[0] It is important to consider that the resulting order of relations may affect the application of other rules in some implementations. For instance, the rules "SEM(A;B):=SEM(C;D)SEM(E;F);" and "SEM(A;B):= SEM(E;F)SEM(C;D);" will provide the same result, but the relation "SEM(C;D)" may be listed before "SEM(E;F)" in the first case, and after it in the second case. This means that a general rule like SEM(;):=SYN(;);, which would be applicable to both generated relations, will be applied first to "SEM(C;D)" in the first case, and to "SEM(E;F)" in the second case.

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Grammar Specs

Contents

Basic symbols

Basic concepts

Nodes

Properties of nodes

Relations

Properties of relations

Hyper-nodes

Properties of hyper-nodes

Hyper-relations

Properties of hyper-relations

Types of rules

Transformation rules

Types of Transformation Rules

List-to-List Rules

Tree-to-Tree Rules

Network-to-Network Rules

List-to-Tree Rules

Tree-to-List Rules

Tree-to-Network Rules

Network-to-Tree Rules

Transformations over nodes

Altering nodes

Deleting nodes

Creating nodes

Duplicating (cloning) nodes

Merging nodes (&)

Splitting nodes (retokenization)

Transformations over hyper-nodes

Altering hyper-nodes

Deleting hyper-nodes

Creating hyper-nodes

Extracting nodes out of hyper-nodes

Transformations over relations and hyper-relations

Creating hyper-relations

Transforming hyper-relations into simple relations

Special types of transformation rules

Retrieving entries in the dictionary (?)

Triggering rules (!)

General properties of transformation rules

Formal Syntax of Transformation Rules

Disambiguation Rules

Network Disambiguation Rules

Examples

Use

Tree Disambiguation Rules

Examples

Use

List Disambiguation Rules

Examples

Use

Formal Syntax of Disambiguation Rules

Indexes

Examples of Rules

LL RULES

LT RULES

TL Rules

TT or NN Rules

Notes

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