TextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models

2022-10-01 · COLING (TextGraphs) 2022 10 · Liubov Kovriguina, Roman Teucher, Robert Wardenga

Automated theorem proving can benefit a lot from methods employed in natural language processing, knowledge graphs and information retrieval: this non-trivial task combines formal languages understanding, reasoning, similarity search. We tackle this task by enhancing semantic similarity ranking with prompt engineering, which has become a new paradigm in natural language understanding. None of our approaches requires additional training. Despite encouraging results reported by prompt engineering approaches for a range of NLP tasks, for the premise selection task vanilla re-ranking by prompting GPT-3 doesn’t outperform semantic similarity ranking with SBERT, but merging of the both rankings shows better results.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Automated Theorem Proving Information Retrieval Knowledge Graphs Natural Language Understanding Prompt EngineeringRe-RankingRetrieval Semantic Similarity Semantic Textual Similarity

Methods 이 논문이 사용한 방법론

SBERT 설명 없음

SNLP at TextGraphs 2022 Shared Task: Unsupervised Natural Language Premise Selection in Mathematical Texts Using Sentence-MPNet

2022-10-01 · COLING (TextGraphs) 2022 10 · Paul Trust, Provia Kadusabe, Haseeb Younis, Rosane Minghim 외

This paper describes our system for the submission to the TextGraphs 2022 shared task at COLING 2022: Natural Language Premise Selection (NLPS) from mathematical texts. The task of NLPS is about selecting mathematical st…

Mathematical Proofs Semantic Similarity Semantic Textual Similarity Sentence

IJS at TextGraphs-16 Natural Language Premise Selection Task: Will Contextual Information Improve Natural Language Premise Selection?

2022-10-01 · COLING (TextGraphs) 2022 10 · Thi Hong Hanh Tran, Matej Martinc, Antoine Doucet, Senja Pollak

Natural Language Premise Selection (NLPS) is a mathematical Natural Language Processing (NLP) task that retrieves a set of applicable relevant premises to support the end-user finding the proof for a particular statement…

TextGraphs 2022 Shared Task on Natural Language Premise Selection

2022-10-01 · COLING (TextGraphs) 2022 10 · Marco Valentino, Deborah Ferreira, Mokanarangan Thayaparan, André Freitas 외

The Shared Task on Natural Language Premise Selection (NLPS) asks participants to retrieve the set of premises that are most likely to be useful for proving a given mathematical statement from a supporting knowledge base…

Premise Selection in Natural Language Mathematical Texts

2020-07-01 · ACL 2020 6 · Deborah Ferreira, Andr{\'e} Freitas

The discovery of supporting evidence for addressing complex mathematical problems is a semantically challenging task, which is still unexplored in the field of natural language processing for mathematical text. The natur…

Link Prediction

Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving

2022-10-01 · COLING (TextGraphs) 2022 10 · Doratossadat Dastgheib, Ehsaneddin Asgari

Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic infor…

Automated Theorem Proving Information Retrieval Keyword Extraction Retrieval