IDL-Expressions: A Formalism for Representing and Parsing Finite Languages in Natural Language Processing

HPE：通过混合问题解析与执行回答基于文本的复杂问题

HPE:Answering Complex Questions over Text by Hybrid Question Parsing and Execution

本文提出HPE框架，通过将复杂问题解析为H-expression中间表示并结合混合执行器，在文本问答中实现了神经与符号方法的优势互补，在多种设置下优于现有方法且提升了可解释性。

A Diagram Is Worth A Dozen Images

Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural images has been extensively studied in computer vision, while diagram understanding has received little attention. In this paper, we study the problem of diagram interpretation and reasoning, the challenging task of identifying the structure of a diagram and the semantics of its constituents and their relationships. We introduce Diagram Parse Graphs (DPG) as our representation to model the structure of…

Using a Diathesis Model for Semantic Parsing

This paper presents a semantic parsing approach for unrestricted texts. Semantic parsing is one of the major bottlenecks of Natural Language Understanding (NLU) systems and usually requires building expensive resources not easily portable to other domains. Our approach obtains a case-role analysis, in which the semantic roles of the verb are identified. In order to cover all the possible syntactic realisations of a verb, our system combines their argument structure with a set of general semantic labelled diatheses models. Combining them, the system builds a set of syntactic-semantic patterns w…

量子自然语言处理

Quantum Natural Language Processing

本文综述量子自然语言处理领域现状，考察词嵌入、序列模型等技术，提出文本编码的新量子设计，并指出现代AI的“幻觉”源于对事实概念化的误解。

使用大型语言模型在知识图谱上进行多跳问答

Multi-hop Question Answering over Knowledge Graphs using Large Language Models

本文评估了大型语言模型在多跳知识图谱问答中的能力，针对不同规模和性质的知识图谱提出相应的信息提取与输入策略，并在六个知识图谱上验证了信息检索和语义解析方法均可与LLM结合取得有竞争力的效果。

从对话到图表：用于加速业务流程原型设计的自然语言任务与关系抽取

From Dialogue to Diagram: Task and Relationship Extraction from Natural Language for Accelerated Business Process Prototyping

针对自然语言转结构化流程模型的难题，提出融合依存分析、NER、SVO结构、语义工具及神经共指消解的方案，可将文本转为BPMN图表，减少人工成本与误差。