Language is multifaceted. A given utterance can be re-expressed in equivalent
forms, and its implicit and explicit content support various logical and
pragmatic inferences. When processing an utterance, we consider these different
aspects, as mediated by our interpretive goals -- understanding that "it's dark
in here" may be a veiled direction to turn on a light. Nonetheless, NLP methods
typically operate over the surface form alone, eliding this nuance.
In this work, we represent language with language, and direct an LLM to
decompose utterances into logical and plausible inferences. The reduced
complexity of the decompositions makes them easier to embed, opening up novel
applications. Variations on our technique lead to state-of-the-art improvements
on sentence embedding benchmarks, a substantive application in computational
political science, and to a novel construct-discovery process, which we
validate with human annotations.

该研究使用 LLM 将话语分解为逻辑和可信推理以及应用该技术改善了句子嵌入基准，推动着计算政治学和构建发现过程的前进。

显式化内含信息: NLP 中内含信息的一等公民

Making the Implicit Explicit: Implicit Content as a First Class Citizen  in NLP

Comparative constructions play an important role in natural language
inference. However, attempts to study semantic representations and logical
inferences for comparatives from the computational perspective are not well
developed, due to the complexity of their syntactic structures and inference
patterns. In this study, using a framework based on Combinatory Categorial
Grammar (CCG), we present a compositional semantics that maps various
comparative constructions in English to semantic representations and introduces
an inference system that effectively handles logical inference with
comparatives, including those involving numeral adjectives, antonyms, and
quantification. We evaluate the performance of our system on the FraCaS test
suite and show that the system can handle a variety of complex logical
inferences with comparatives.

基于组合范畴语法（CCG）的框架，本文提出了一种构成语义映射的方式来处理英语中各种比较结构，并引入了一个有效处理比较逻辑推断的推断系统，包括涉及数词形容词、反义词和量化词的比较。我们在 FraCaS 测试套件上评估了我们系统的性能，并表明该系统可以处理各种复杂的比较逻辑推断。

基于 CCG 的比较句组合语义推理系统

A CCG-based Compositional Semantics and Inference System for  Comparatives

The knowledge base paradigm aims to express domain knowledge in a rich formal
language, and to use this domain knowledge as a knowledge base to solve various
problems and tasks that arise in the domain by applying multiple forms of
inference. As such, the paradigm applies a strict separation of concerns
between information and problem solving. In this paper, we analyze the
principles and feasibility of the knowledge base paradigm in the context of an
important class of applications: interactive configuration problems. In
interactive configuration problems, a configuration of interrelated objects
under constraints is searched, where the system assists the user in reaching an
intended configuration. It is widely recognized in industry that good software
solutions for these problems are very difficult to develop. We investigate such
problems from the perspective of the KB paradigm. We show that multiple
functionalities in this domain can be achieved by applying different forms of
logical inferences on a formal specification of the configuration domain. We
report on a proof of concept of this approach in a real-life application with a
banking company. To appear in Theory and Practice of Logic Programming (TPLP).

本文分析了知识库范式在交互式配置问题中的原则和可行性，并表明在形式化配置领域的规范化说明上应用不同形式的逻辑推理，可以实现该领域的多种功能。通过在银行业的实际应用实现了该方法的概念验证。