UNLization
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== UNLization units == | == UNLization units == | ||
− | *Word-driven UNLization (the UNLization does not preserve any structure of the source document except | + | The process of UNLization may focus different units, as follows: |
− | *Sentence-driven UNLization (the UNLization | + | *Word-driven UNLization (the UNLization does not preserve any structure of the source document except relations between concepts) |
− | *Text-driven UNLization (the UNLization | + | *Sentence-driven UNLization (the UNLization represents the source document as a list of non-semantically related sentences) |
+ | *Text-driven UNLization (the UNLization represents the source document as a network of semantically related sentences) | ||
== UNLization paradigms == | == UNLization paradigms == |
Revision as of 23:19, 13 December 2010
UNLization, formerly known as enconversion, is the process of "representing" a natural language structure into UNL. This representation should be understood as a interpretation rather than as a translation of the source document, in the sense it is not necessarily committed to its linguistic structure (such as lexical choice and syntax) but to its semantic structure only (it must replicate concepts and relations between concepts conveyed by the linguistic structure).
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UNLization units
The process of UNLization may focus different units, as follows:
- Word-driven UNLization (the UNLization does not preserve any structure of the source document except relations between concepts)
- Sentence-driven UNLization (the UNLization represents the source document as a list of non-semantically related sentences)
- Text-driven UNLization (the UNLization represents the source document as a network of semantically related sentences)
UNLization paradigms
The process of UNLization may follow several different paradigms, as follows:
- Language-based UNLization (based mainly in a NL-UNL dictionary and NL-UNL grammar)
- Knowledge-based UNLization (based mainly in the UNL Knowledge Base)
- Example-based UNLization (based mainly in the UNL Example Base))
- Memory-based UNLization (based mainly in the UNL-NL UNlization Memory)
- Statistical-based UNLization (based mainly in statistical predictions derived from UNL-NL corpora)
- Dialogue-based UNLization (based mainly in the interaction with the user)
The actual UNLization is normally hybrid and may combine several of the strategies above.
Recall
The process of UNLization may target the whole source document or only parts of it (e.g. main clauses):
- Full UNLization (the whole source document is UNLized)
- Partial (or chunk) UNLization (only a part of the source document is UNLized)
- Peter killed Mary with a knife yesterday morning.
- Full UNLization: Peter killed Mary with a knife yesterday morning.
- Partial UNLization: Peter killed Mary.
Precision
The process of UNLization may target the deep semantic structure of the source document (i.e., the resulting semantic structure replicates the syntactic structure of the original) or only its surface structure (the resulting semantic structure does not preserve the syntactic structure of the original)
- Deep UNLization (the UNLization focus the deep semantic structure of the source document)
- Shallow UNLization (the UNLization focus the surface semantic structure of the source document)
Syntactic structures are preserved in the UNL document by the use of syntactic attributes (such as @passive, @topic, etc) or by hyper-nodes (i.e., scopes). For some purposes, as translation, UNLization may require syntactic details; for others, such as information retrieval, syntactic structures at this level are not normally necessary:
- Mary was killed by Peter
- Shallow UNLization: Peter killed Mary
- Deep UNLization: [Peter killed Mary].@passive
- Mary saw Peter going to Paris.
- Shallow UNLization: Mary saw Peter & Peter was going to Paris
- Deep UNLization: Mary saw [Peter going to Paris].
- As for the little girl, the dog licked her.
- Shallow UNLization: the dog licked the little girl
- Deep UNLization: the dog licked [the little girl].@topic
Level
The process of UNLization may target represent literal meanings (locutionary content) or non-literal meanings (ilocutionary content).
- Locutionary (the UNLization represents only the literal meaning)
- Ilocutionary (the UNLization represents also non-literal meanings, including speech acts)
The ilocutionary force may be represented by figure of speech and speech acts attributes:
- It is as soft as concrete
- Locutionary level: it is as soft as concrete
- Ilocutionary level: [it is as soft as concrete].@irony
- Can you pass me the salt?
- Locutionary level: can you pass me the salt?
- Ilocutionaruy level: [pass me the salt].@request
UNLization challenges
The UNL document will not contain the semantic ambiguities of the original, and will only encode one of its possible semantic realisations, preferably the most frequent one:
- The bank crashed.
- UNL is not able to preserve the lexical ambiguity of the word "bank" in the sentence above. The UNL representation will necessarily choose between one of the possible concepts conveyed by the English word "bank".
- The boy saw the girl with binoculars
- UNL is not able to represent the syntactic ambiguity of the sentence above. The UNL representation will necessarily choose between one of the possible syntactic structures of the sentence.