Tokenization

Revision as of 15:11, 18 April 2012

Tokenization is the process of segmenting the input into "tokens" (processing units).

General principles

In the UNL framework, tokenization follows the principles below:

1. The tokenization algorithm goes from left to right.
2. Except for digits, the tokenization algorithm is strictly dictionary-based (spaces and punctuation signs have to be inserted in the dictionary in order to be treated as non-temporary entries)
3. The tokenization algorithm tries to match first the longest entries in the dictionary.
4. The tokenization algorithm observes the frequency of the entries informed the dictionary (the highest frequent entries come first).
5. The tokenization algorithm observes the order of the entries in the dictionary (the system selects the first to appear in case of same frequency)
6. The tokenization algorithm assigns the feature TEMP (temporary) to the strings that were not found in the dictionary.
7. The tokenization algorithm blocks tokens or sequences of tokens prohibited by disambiguation rules.
8. In case of several possible candidates, the tokenization algorithm picks the ones induced by disambiguation rules, if any.

Tokenization of natural language input

Tokenization of spaces, punctuation signs and symbols

The tokenization does not have any system-defined tokens except for digits. Any token has be to inserted in the dictionary in order to recognized as a non-temporary entry.

Tokenization of digits

Any sequence of digits is considered one single token and receives the feature DIGIT. The UW is considered to be equal to the headword.

Tokenization of temporary entries

Any sequence of characters except digits (and including special symbols, such as space and punctuation signs) not found in the dictionary is considered a temporary entry and receives the feature TEMP. The UW is considered to be empty.

Tokenization of natural language entries

Dictionary

[abcde]{}""(...)<...>;

[abcd]{}""(...)<...>;

[bcde]{}""(...)<...>;

[abc]{}""(...)<...>;

[bcd]{}""(...)<...>;

[cde]{}""(...)<...>;

[ab]{}""(...)<...>;

[bc]{}""(...)<...>;

[cd]{}""(...)<...>;

[de]{}""(...)<...>;

[a]{}""(A1,...)<...>;

[a]{}""(A2,...)<...>;

[b]{}""(B1,...)<...>;

[b]{}""(B2,...)<...>;

[c]{}""(C1,...)<...>;

[c]{}""(C2,...)<...>;

[d]{}""(D1,...)<...>;

[d]{}""(D2,...)<...>;

[e]{}""(E1,...)<...>;

[e]{}""(E2,...)<...>;

Case 1

input: "abcde"

disambiguation rule: NONE

tokenization output: [abcde] (the longest entry in the dictionary)

Case 2

input: "abcde"

disambiguation rule: ("abcde")=0; (prohibits the sequence "abcde")

tokenization output: [abcd][e] (the second longest possibility from left to right according to the dictionary)

Case 3

input: "abcde"

disambiguation rules: ("abcde")=0;("abcd")("e")=0;

tokenization output: [a][bcde] (the third longest possibility from left to right according to the dictionary)

Case 4

input: "abcde"

disambiguation rules: ("abcde")=0;("abcd")("e")=0;("a")("bcde")=0;

tokenization output: [abc][de] (the fourth longest possibility from left to right according to the dictionary)

Case 5

input: "abcde"

disambiguation rules: ("/.{3,5}/")=0; (prohibits any token made of 3, 4 or 5 characters)

tokenization output: [ab][cd][e]

Case 6

input: "abXcYde"

disambiguation rule: NONE

tokenization output: [ab][X][c][Y][de] (where [X] and [Y] are temporary entries)

Properties of tokenization

Positive disambiguation rules only apply over candidates to the same position with the same length

Case 7

input: "abcde"

disambiguation rule: ("abcd")("e")=100; (induces the sequence [abcd][e])

tokenization output: [abcde] (positive disambiguation rules do not prevail over the principle of longest first)

Case 8

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (prohibits any token made of 2, 3, 4 or 5 characters)

tokenization output: [a,A1][b,B1][c,C1][d,D1][e,E1] (among the candidates, these entries come first in the dictionary)

Case 9

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (A2)(B2)=1; (induces the sequence [A2][B2])

tokenization output: [a,A2][b,B2][c,C1][d,D1][e,E1] (A2 and B2 were chosen instead of A1 and B1)

Positive disambiguation rules apply according to their probability and, inside the same probability, according to their order in the grammar

Case 10

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (A2)(B2)=1; (A2)(B1)=1; (induces the sequence [A2][B1])

tokenization output: [a,A2][b,B2][c,C1][d,D1][e,E1] (the rule [A2][B2] has the some probability as [A2][B1] and comes first in the grammar)

Case 11

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (A2)(B2)=1; (A2)(B1)=2; (induces the sequence [A2][B1])

tokenization output: [a,A2][b,B1][c,C1][d,D1][e,E1] (the priority of the rule [A2][B1] is higher than [A2][B2])

Case 12

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (A2)(B2)=1; (B1)(C2)=2; (induces the sequence [A2][B1])

tokenization output: [a,A1][b,B1][c,C2][d,D1][e,E1] (the priority of the rule [B1][C2] is higher than [A2][B2])

The attribute #FINAL is used to indicate context

Case 13

input: "abcde"

disambiguation rule: ("/.{2,5}/")=0; (A2)(B2)=1; (B1,#FINAL)(C2)=5; (if B1 is fixed, C2 must be chosen)

tokenization output: [a,A2][b,B2][c,C1][d,D1][e,E1] (the same as case 11; compare with case 12 - note that the rule (B1,#FINAL)(C2) does not induce the choice of B1; it applies only to C2, i.e., it indicates that, if B1, then C2)

The tokenization algorithm backtracks in case of dead-ends.

In case of backtracking, the tokenization starts merging nodes from left to right, but considering their size, i.e., the shortest combinations appear first.

Case 14

input: "abcde"

dictionary:

[a]{}""(...)<...>;
[b]{}""(...)<...>;
[c]{}""(...)<...>;
[d]{}""(...)<...>;
[e]{}""(...)<...>;

disambiguation rule: ("a")("b")("c")("d")("e")=0;

tokenization output: [ab][b][c][d][e] (the first combination of shortest temporary nodes from left to right after [a][b][c][d][e], which was blocked by the disambiguation rule. Note that [ab] is not in the dictionary and, therefore, will be treated as TEMP)

Retokenization

Only temporary nodes (i.e., nodes having the feature TEMP) may be split, but the feature TEMP may be assigned to any node.
Examples:

• Infixation

("abcd",INFIXED,^TEMP):=(%x,+TEMP); (assigns TEMP to the node %x if it is not TEMP and make it available for retokenization)
After that, the node may be retokenized by rules such as:
("ab",INFIXED,%x)("cd",INFIXED,%y):=(%x)("1",%z)(%y); (the node ("abcd") becomes ("ab")("1")("cd"))
In order to merge the node again, we have to use a merge rule:
("ab",INFIXED,%x)(%z)("cd",INFIXED,%y):=(%x&%z&%y,-INFIXED,+REMOVE_TEMP); (the three nodes ("ab")("1")("cd") become a single node ("ab1cd")
Then, we may remove the feature TEMP:
(REMOVE_TEMP,%x,TEMP):=(%x,-TEMP);

• Duplication of the last character

("abcd",DLC,%x,^TEMP):=(%x,+TEMP); (assigns TEMP to the node %x if it is not TEMP and make it available for retokenization)
After that, the node may be retokenized by rules such as:
("/.+/",DLC,%x)("/./",DLC,%y):=(%x)(%y)(%y); (the node ("abcd") becomes ("abc")("d")("d"))
In order to merge the node again, we have to use a merge rule:
(DLC,%x)(DLC,%z)(DLC,%y):=(%x&%y&%z,-DLC,+REMOVE_TEMP); (the three nodes ("abc")("d")("d") become a single node ("abcdd")
Then, we may remove the feature TEMP:
(REMOVE_TEMP,%x,TEMP):=(%x,-TEMP);
Observations:

Splitting operations affect only strings. All the features of the source node, including headword and UW, are preserved in the target nodes

Given the node ("abcd",[abcd],[[abcd]],A),
the retokenization rule ("ab",%x)("cd",%y):=(%x)("1",%z)(%y);
does not affect the original headword, UW and feature, i.e.:
the nodes ("ab") and ("cd") still have, each one, the features [abcd],[[abcd]],A.

Tokenization of UNL input

Case 15

Dictionary:

[x]{}"x"(...)<...>;
[xa]{}"x.@a"(...)<...>;
[xab]{}"x.@a.@b"(...)<...>;
[y]{}"y"(...)<...>;

Input:

agt(x.@a.@b,y)

Tokenization output

agt([xab],[y])