Toward Automatic Compilation of Phrasal Thesaurus

Atsushi Fujita
Satoshi SatoGraduate School of Engineering, Nagoya University{fujita,ssato}@nuee.nagoya-u.ac.jp

1 Introduction

to divide them according to their productivity andrequired knowledge, and then separately develop resources to compute them.

Thesaurus, which links between linguistic expressions (or concepts) based on various semantic relations, is one of the most fundamental semantic resources in a broad range of NLP tasks. A lot ofwork has been carried out relying on thesauri, suchas WordNet (Miller, 1995) and automatically createdversions of it. The entries of most existing thesauri
are either single words or word sequences includingphrasal verbs and canned phrases. However, they
may not be almighty in dealing with meaning, because meaning of polysemous word is determined
only when it is used in some context, and meaningof phrase, clause, and sentence is determined based
not only on those of its constituent words but also on
its construction.
For a more precise semantic computing, we haveproposed phrasal thesaurus, which regards phrases
as entries (Fujita et al., 2007). While the term“phrase” generally refers to word sequences, such asphrasal verbs and canned phrases, in our study, thenotion also includes predicate phrases those involve
complements. Among various types of semantic relations between phrases, we have been addressing
mainly paraphrases and textual entailment.
This paper describes the direction and current status of our study on compiling phrasal thesaurus.

Synonym pairs (e.g., “comfort” ⇔ “console”) andidiom/literal paraphrases (e.g., “kick the bucket” ⇔“die”) are typical examples of non-productive paraphrases. As they cannot be represented with abstract patterns, a huge amount of fully lexicalized
paraphrase pairs should be compiled into a dictionary statically to realize this class of paraphrases.
State-of-the-art corpus-based techniques for acquiring paraphrases are beneficial to its compilation. Infact, most of the paraphrases that previous work hascollected are classified into this class.
In our study, we are compiling a idiom/literalparaphrase dictionary. So far, we have compiled alist of basic Japanese idioms based on five dictionaries for human, in order to set a goal regarding
its scale; the resultant list consists of 3,629 entries(Sato, 2007). The next step is to collect the counterpart, i.e., literal phrase, for each basic idiom. While
candidate literal phrases can be extracted for a certain portion of idioms from explanatory sentences indictionaries for human, we will also apply automatic
acquisition methods in order to complementarily attain the coverage.

2 Thesaurus of Predicate Phrases

Productive paraphrases

Combination of content words and various constructions coerce us into handling an enormous numberof expressions than word-based thesaurus. In addition, single concept can be conveyed by variousconstructions (Fujita, 2008). Our strategy to attainthe coverage of paraphrases of predicate phrases is

In contrast to non-productive paraphrases, it seems
reasonable to represent the knowledge for productive paraphrases, such as voice/case alternation,
nominalization and light-verb construction, with abstract patterns. For example, the phrasal pair (1a)can be represented with the pattern (1b).

Non-productive paraphrases

(1)a. Employment shows a sharp decrease⇔ Employment decreases sharply
b. XNoun show a YAdjective ZNoun⇔ XNoun verb(ZNoun ) adverb(YAdjective )However, those patterns are not capable of preventing incorrect instantiations of phrasal paraphrases,
because their applicability conditions, such as restrictions for variable slots (e.g., YAdjective andZNoun ), tend to be underspecified. This is fatal, particularly in case of generating paraphrases; for example, the following incorrect paraphrases are generated from the pattern (1b).
(2) a. Statistics show a gradual decline⇔ Statistics decline graduallyb. The data show a specific distribution⇔ ∗ The data distribute specifically
Yet, this descriptive approach guarantees a certain
degree of equivalence by exploring paraphrase instances based on transformation patterns and lexicalfunctions, such as verb(ZNoun ) and adverb(YAdj ).
On the basis of this recognition, we have been
examining the following generate-and-test method,
particularly targeting at Japanese:
Step 1. (Over-)generate syntactic variants based onsyntactic transformation and lexical derivation.
Step 2. Measure how the pair of phrases is likely tobe grammatical and correct as paraphrases byan empirical method.
In the first step, syntactic variants are generatedusing the following three sorts of linguistic knowledge (Fujita et al., 2007):• Transformation patterns that give skeletons ofsyntactic variants, like (1b)• Generation functions that generate a set of thesimplest phrases from 0-2 content words• Lexical functions whose back-end is E NJI: aJapanese Lexical Derivation Database
While the first two resources are fully handcrafted,
the last one is semi-automatically compiled based on
affix patterns, such as “S-i:Adjective ⇒ S-mi:Noun”
for “amai (be sweet)” and “amami (sweetness).”
The database has been enlarged and cleaned up after (Fujita et al., 2007); consequently it consistsof 4,814 pairs of cross-categorial lexical derivatives(3,525 trees containing 8,265 words).
Then, in the second step, each pair of automatically generated phrasal paraphrases are assessedagainst the following criteria that a correct pair ofphrasal paraphrases must fulfill (Fujita and Sato,2008a; Fujita and Sato, 2008b):
Criterion 1. Semantically equivalent
Criterion 2. Substitutable in some context
Criterion 3. Grammatical, respectively
To quantify how the given pair of phrases satisfies
the above criteria, we have examined an empiricalmodel which combines structured N -gram language
models and distributional similarity measures.
Through a series of experiments, our approach
has achieved promising results by coupling constituent similarity based on descriptive knowledge
and contextual similarity computed empirically.

3 Future directions
While we described the motivation and current status of our study on compiling phrasal thesaurus particularly focusing on predicate phrases, we are also
concerned with paraphrasing of functional expressions. Based on T SUTSUJI: a dictionary of Japanesefunctional expressions (Matsuyoshi and Sato, 2008),
we are exploring the multi-word functional expressions, and the interaction between predicate phrases
and functional expressions.

References
Atsushi Fujita, Shuhei Kato, Naoki Kato, and Satoshi Sato.
2007. A compositional approach toward dynamic phrasal
thesaurus. In Proceedings of the ACL-PASCAL Workshop on
Textual Entailment and Paraphrasing (WTEP), pages 151–158.
Atsushi Fujita and Satoshi Sato. 2008a. Computing paraphrasability of syntactic variants using Web snippets. In Proceedings of the 3rd International Joint Conference on Natural Language Processing (IJCNLP), pages 537–544.
Atsushi Fujita and Satoshi Sato. 2008b. A probabilistic modelfor measuring grammaticality and similarity of automatically generated paraphrases of predicate phrases. In Proceedings of the 22nd International Conference on Computational Linguistics (COLING), pages 225–232.
Atsushi Fujita. 2008. Survey on automatic paraphrasing.
http://paraphrasing.org/.
Suguru Matsuyoshi and Satoshi Sato. 2008. Automatic paraphrasing of Japanese functional expressions using a hierarchically organized dictionary. In Proceedings of the 3rd International Joint Conference on Natural Language Processing (IJCNLP), pages 691–696.
George A. Miller. 1995. WordNet: a lexical database for English. Communications of the ACM, 38(11):39–41.
Satoshi Sato. 2007. Compilation of a comparative list of basic
Japanese idioms from five sources. In Information Processing Society of Japan SIG Notes, NL-178-1, pages 1–6. (inJapanese).