Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition

Table 6 F₁ scores of higher-order CRF models and pi-CRF for each corpora. The first value (‘whole instance’) is F₁ score with whole test set and the second value (‘distanced instance’) is F₁ score evaluated only with instanced having transition dependency between NEs. (bold: best performance, shaded: pi-CRF)

Feature	Models	i2b2 2012		SNUH		CoNLL 2003
		whole instance	distanced instance	whole instance	distanced instance	whole instance	distanced instance
Set 1	2nd-order CRF	69.46	70.88	73.43	72.21	58.34	54.52
	semi-Markov CRF	67.87	68.91	73.44	71.61	37.31	34.13
	high-order CRF	68.38	69.52	73.50	71.69	36.97	33.87
	pi-CRF	67.29	68.43	75.50	74.43	45.54	43.41
Set 2	2nd-order CRF	70.99	72.31	74.31	73.27	73.21	72.26
	semi-Markov CRF	72.19	73.54	76.01	74.87	63.19	63.32
	high-order CRF	71.50	72.74	76.11	74.97	63.56	63.76
	pi-CRF	72.30	73.61	76.20	75.47	69.61	72.31
Set 3	2nd-order CRF	71.75	73.01	75.17	74.05	83.13	83.96
	semi-Markov CRF	69.30	70.73	76.70	75.79	82.47	83.29
	high-order CRF	69.26	70.64	76.73	75.91	82.18	82.80
	pi-CRF	72.58	74.04	76.28	75.45	82.08	82.76

ISSN: 1472-6947