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. 2015 Oct 31;23(2):387–395. doi: 10.1093/jamia/ocv113

Table 1.

Core features per type of relation

Feature Description DocTimeRel Event-Event Relations Event-Time Relations
Tokens The first and the last word of each concept, all words covered by a concept as a bag, bag-of-words around each concept for a window of [−3, 3], bag-of-words between 2 concepts, and the number of words between 2 concepts (for the THYME corpus, the headword event is expanded to the immediately enclosing NP and the NP becomes the anchor for the token features)
Part-of-speech tags The Penn Treebank POS tags of each concept as a bag
Event attributes All event-related attributes such as polarity, modality, and type. Note that DocTimeRel is also an event attribute, and is used for reasoning on the within-sentence relations.
UMLS feature UMLS semantic types of each concept as features
Dependency path The dependency path between 2 concepts and the number of dependency nodes in-between
Overlapped head If 2 concepts share the same headword
Temporal attributes The class type of a time expression, eg, “Date,” “Time,” “Duration,” etc.
Special words Any special words from the time lexicon developed by the NRCC24 that the concepts or the context in-between contain
Nearest flag If the event-time pair in question is the closest among all pairs in the same sentence
Conjunction feature If there is any conjunction word between the arguments
Nearby verb’s part-of-speech tag The Penn Treebank POS tags of the verbs within the same sentence
Section ID The header of the section containing the target concept
Closest verb The tokens and Penn Treebank POS tags of the closest verb to the target concept within the same sentence
TimeX feature The tokens and attributes of the closest time expression in the same sentence

Abbreviations: DocTimeRel, document time relation; NP, Noun Phrase; THYME, temporal histories of your medical events; POS, part-of-speech; UMLS, unified medical language system; NRCC, National Research Council Canada; ID, Identifier.