Paraphrasing Questions Using Given and new information
Summary
The paper describes the paraphrase module of CO-OP (Kaplan 1979), a natural-language question-answering front end for databases aimed at casual users. Before the system searches the database, it restates the user's question in English so the user can catch misinterpretations. This is the only error check available to non-experts. The paraphraser takes the parser's syntactic tree and uses a transformational grammar instead of canned templates. It addresses two problems: ambiguous relative-clause attachment, and the risk of simply echoing the original wording. Drawing on the given/new distinction (Halliday, Krizkova, Firbas, Chafe), it divides a question into three parts. The given material becomes an "assuming that" clause that exposes the user's existential presuppositions. The new material is the bare wh-question plus the modifiers of the interrogative item. The design is domain-independent and needs no changes when the database changes. In development, the module was useful for spotting incorrect parses. However, no evaluation with real users is reported.
Key points
- The paraphrase breaks a question into three components: given information, the questioner's lack of knowledge, and the "angle" (modifiers of the wh-word).
- Reordering clauses removes attachment ambiguity. For example, the question about books on computers "dating from the '60s" yields distinct paraphrases for each reading.
- The paper contrasts its approach with the template-based PLANES (Waltz 1978) and RENDEZVOUS (Codd 1978) paraphrasers. RENDEZVOUS uses FIND, EXIST and COUNT query headers. Templates are tied to a specific domain and interact unpredictably.
- In CO-OP, only the lexicon and the database schema contain domain knowledge. The paraphraser itself is purely syntactic, and adding semantic paraphrasing (synonyms, idioms) is left for future work.
- The work was done at the University of Pennsylvania, with support from an IBM Fellowship and NSF grants MCS 78-08401 and MCS 79-19171.
Cited by
- A Survey of Paraphrasing and Textual Entailment Methods
- Neural Syntactic Preordering for Controlled Paraphrase Generation
- A Deep Generative Framework for Paraphrase Generation
- ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation
- Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
- Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation
- Syntax-Guided Controlled Generation of Paraphrases
- Paraphrase Generation with Deep Reinforcement Learning
- Neural Paraphrase Generation with Stacked Residual LSTM Networks
- Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity
- Paraphrasing as Zero-shot Translation with Feature-guided Diversity Enhancement
Cite
@article{mckeown1983paraphrasing,
title = {{Paraphrasing Questions Using Given and new information}},
author = {McKeown, Kathleen R.},
journal = {Computational Linguistics},
year = {1983},
doi = {10.7916/d80c55kd},
url = {https://doi.org/10.7916/d80c55kd}
}References
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