Any natural language expression of a set of facts - that can be represented as a knowledge graph - will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore, propose a specific pipeline that can be applied to produce linguistic narratives from knowledge graphs using an ontological layer and corresponding rules that turn a knowledge graph into a semantic specification for natural language generation. Critically, narratives are seen as necessarily committing to specific perspectives taken on the facts presented. We show how this most commonly neglected facet of producing summaries of facts can be brought under control.

Narrativizing Knowledge Graphs

Santagiustina C.
2022-01-01

Abstract

Any natural language expression of a set of facts - that can be represented as a knowledge graph - will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore, propose a specific pipeline that can be applied to produce linguistic narratives from knowledge graphs using an ontological layer and corresponding rules that turn a knowledge graph into a semantic specification for natural language generation. Critically, narratives are seen as necessarily committing to specific perspectives taken on the facts presented. We show how this most commonly neglected facet of producing summaries of facts can be brought under control.
Artificial Intelligence Technologies for Legal Documents and Knowledge Graph Summarization 2022
File in questo prodotto:
File Dimensione Formato  
Narrativizing Knowledge Graphs.pdf

accesso aperto

Descrizione: articolo: Narrativizing Knowledge Graphs
Tipologia: Versione dell'editore
Licenza: Accesso libero (no vincoli)
Dimensione 1.26 MB
Formato Adobe PDF
1.26 MB Adobe PDF Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5012206
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact