Composing Conversational Negation
- URL: http://arxiv.org/abs/2107.06820v1
- Date: Wed, 14 Jul 2021 16:24:41 GMT
- Title: Composing Conversational Negation
- Authors: Razin A. Shaikh and Lia Yeh and Benjamin Rodatz and Bob Coecke
- Abstract summary: We compose the negations of single words to capture the negation of sentences.
We also describe how to model the negation of words whose meanings evolve in the text.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Negation in natural language does not follow Boolean logic and is therefore
inherently difficult to model. In particular, it takes into account the broader
understanding of what is being negated. In previous work, we proposed a
framework for negation of words that accounts for `worldly context'. In this
paper, we extend that proposal now accounting for the compositional structure
inherent in language, within the DisCoCirc framework. We compose the negations
of single words to capture the negation of sentences. We also describe how to
model the negation of words whose meanings evolve in the text.
Related papers
- Generating Diverse Negations from Affirmative Sentences [0.999726509256195]
Negations are important in real-world applications as they encode negative polarity in verb phrases, clauses, or other expressions.
We propose NegVerse, a method that tackles the lack of negation datasets by producing a diverse range of negation types.
We provide new rules for masking parts of sentences where negations are most likely to occur, based on syntactic structure.
We also propose a filtering mechanism to identify negation cues and remove degenerate examples, producing a diverse range of meaningful perturbations.
arXiv Detail & Related papers (2024-10-30T21:25:02Z) - Paraphrasing in Affirmative Terms Improves Negation Understanding [9.818585902859363]
Negation is a common linguistic phenomenon.
We show improvements with CondaQA, a large corpus requiring reasoning with negation, and five natural language understanding tasks.
arXiv Detail & Related papers (2024-06-11T17:30:03Z) - Revisiting subword tokenization: A case study on affixal negation in large language models [57.75279238091522]
We measure the impact of affixal negation on modern English large language models (LLMs)
We conduct experiments using LLMs with different subword tokenization methods.
We show that models can, on the whole, reliably recognize the meaning of affixal negation.
arXiv Detail & Related papers (2024-04-03T03:14:27Z) - Unsupervised Mapping of Arguments of Deverbal Nouns to Their
Corresponding Verbal Labels [52.940886615390106]
Deverbal nouns are verbs commonly used in written English texts to describe events or actions, as well as their arguments.
The solutions that do exist for handling arguments of nominalized constructions are based on semantic annotation.
We propose to adopt a more syntactic approach, which maps the arguments of deverbal nouns to the corresponding verbal construction.
arXiv Detail & Related papers (2023-06-24T10:07:01Z) - CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about
Negation [21.56001677478673]
We present the first English reading comprehension dataset which requires reasoning about the implications of negated statements in paragraphs.
CONDAQA features 14,182 question-answer pairs with over 200 unique negation cues.
The best performing model on CONDAQA (UnifiedQA-v2-3b) achieves only 42% on our consistency metric, well below human performance which is 81%.
arXiv Detail & Related papers (2022-11-01T06:10:26Z) - Transparency Helps Reveal When Language Models Learn Meaning [71.96920839263457]
Our systematic experiments with synthetic data reveal that, with languages where all expressions have context-independent denotations, both autoregressive and masked language models learn to emulate semantic relations between expressions.
Turning to natural language, our experiments with a specific phenomenon -- referential opacity -- add to the growing body of evidence that current language models do not well-represent natural language semantics.
arXiv Detail & Related papers (2022-10-14T02:35:19Z) - Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal
Negation [59.307534363825816]
Negation is poorly captured by current language models, although the extent of this problem is not widely understood.
We introduce a natural language inference (NLI) test suite to enable probing the capabilities of NLP methods.
arXiv Detail & Related papers (2022-10-06T23:39:01Z) - Conversational Negation using Worldly Context in Compositional
Distributional Semantics [0.0]
Given a word, our framework can create its negation similar to how humans perceive negation.
We propose and motivate a new logical negation using matrix inverse.
We conclude that the combination of subtraction negation and phaser in the basis of the negated word yields the highest Pearson correlation of 0.635 with human ratings.
arXiv Detail & Related papers (2021-05-12T16:04:36Z) - Understanding by Understanding Not: Modeling Negation in Language Models [81.21351681735973]
Negation is a core construction in natural language.
We propose to augment the language modeling objective with an unlikelihood objective that is based on negated generic sentences.
We reduce the mean top1 error rate to 4% on the negated LAMA dataset.
arXiv Detail & Related papers (2021-05-07T21:58:35Z) - Provable Limitations of Acquiring Meaning from Ungrounded Form: What
will Future Language Models Understand? [87.20342701232869]
We investigate the abilities of ungrounded systems to acquire meaning.
We study whether assertions enable a system to emulate representations preserving semantic relations like equivalence.
We find that assertions enable semantic emulation if all expressions in the language are referentially transparent.
However, if the language uses non-transparent patterns like variable binding, we show that emulation can become an uncomputable problem.
arXiv Detail & Related papers (2021-04-22T01:00:17Z) - Negation in Cognitive Reasoning [0.5801044612920815]
Negation is an operation in formal logic and in natural language.
One task of cognitive reasoning is answering questions given by sentences in natural language.
arXiv Detail & Related papers (2020-12-23T13:22:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.