A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure

Liana Ermakova (1) , Josiane Mothe (2, 3) , Anton Firsov (4)

1 LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés
2 IRIT-SIG - Systèmes d’Informations Généralisées
3 UT2J - Université Toulouse - Jean Jaurès
4 Perm State University

Sentence ordering (SO) is a key component of verbal ability. It is also crucial for automatic text generation. While numerous researchers developed various methods to automatically evaluate the informativeness of the produced contents, the evaluation of readability is usually performed manually. In contrast to that, we present a self-sufficient metric for SO assessment based on text topic-comment structure. We show that this metric has high accuracy.

Mots clés: Text coherence; Evaluation; Information retrieval; Topic-comment structure; Information structure; Sentence ordering; Topic; Comment

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Liana Ermakova, Josiane Mothe, Anton Firsov. A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure. 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), Aug 2017, Tokyo, Japan. pp. 1061-1064, ⟨10.1145/3077136.3080720⟩. ⟨hal-01873782⟩