Speculation Detection
Speculation detection, also known as hedging analysis, is a natural-language-processing task that identifies epistemic uncertainty markers — words and phrases such as 'may', 'possibly', 'it is suggested that' — within scientific, biomedical, and news texts. Formalised by Hyland (1996) for scientific writing and benchmarked by the CoNLL-2010 shared task, the method reveals where authors signal incomplete knowledge, tentativeness, or distance from a claim rather than asserting facts directly.
Izvorni zapis
Citati kopirani doslovno iz izvornog zapisa metode. Ne impliciraju nikakvu provjeru na razini tvrdnje.
- Hyland, K. (1996). Writing Without Conviction? Hedging in Science Research Articles. Applied Linguistics, 17(4), 433-454. · DOI 10.1093/applin/17.4.433
- Farkas, R. et al. (2010). The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text. Proceedings of the Fourteenth Conference on Computational Natural Language Learning — Shared Task (CoNLL 2010), 1-12. · URL
Uređene tvrdnje
Tvrdnje pohranjene u knjigu dokaza, svaka s vlastitom procjenom.
Ovaj prikaz ne izmišlja procjenu tvrdnje kada knjiga dokaza nema nijednu.
Povezane metode
Generirano iz grafa metode i prikazano kao strojno predložene relacije — ne implicira se nikakva tvrdnja dokaza.