Using Bloom’s Taxonomy to Classify Question Complexity
Herausgeber Sammlung:
Abbas, Mourad; Freihat, Abed Alhakim
Titel Konferenzpublikation:
Proceedings of The Fourth International Conference on Natural Language and Speech Processing (ICNLSP 2021)
Konferenztitel:
International Conference on Natural Language and Speech Processing (4., 2021, Trient)
Tagungsort:
Trient, Italien; Virtuell
Jahr der Konferenz:
2021
Datum Beginn der Konferenz:
12.11.2021
Datum Ende der Konferenz:
13.11.2021
Verlagsort:
Stroudsburg, PA
Verlag:
Association for Computational Linguistics
Jahr:
2021
Seiten von - bis:
285-289
Sprache:
Englisch
Abstract:
Question answering is widespread and a vari- ety of answer taxonomies exists in research that divides responses into simple and com- plex. Multi-hop answering has become pop- ular when the complexity of questions and an- swers increases. However, determining when multi-hop reasoning becomes necessary is not yet clear.
We propose to apply Bloom’s taxonomy to the determination of question complexity in question-answering systems. Originating in pedagogy, Bloom’s taxonomy measures ques- tion complexity to determine learning progress levels. Subsequently, the determined question complexity can help in deciding whether an entity or phrase is sufficient as an answer or whether reasoning chains should be given. «
Question answering is widespread and a vari- ety of answer taxonomies exists in research that divides responses into simple and com- plex. Multi-hop answering has become pop- ular when the complexity of questions and an- swers increases. However, determining when multi-hop reasoning becomes necessary is not yet clear.
We propose to apply Bloom’s taxonomy to the determination of question complexity in question-answering systems. Originating in pedagogy, Bloom’s taxonomy measures ques- tion comp... »