Biomedical named entities being treated as Cardinals about bllip-parser HOT 2 CLOSED

Yes, this is supported! You'll want to use parse_tagged() instead of parse():

You can also parse text with existing POS tags (these act as soft constraints). In this example, token 0 ('Time') should have tag VB and token 1 ('flies') should have tag NNS:

rrp.parse_tagged(['Time', 'flies'], possible_tags={0 : 'VB', 1 : 'NNS'})[0]
ScoredParse('(S1 (NP (VB Time) (NNS flies)))', parser_score=-54.05083561918019, reranker_score=-15.079632500107973)

You don't need to specify a tag for all words: Here, token 0 ('Time') should have tag VB and token 1 ('flies') is unconstrained:

rrp.parse_tagged(['Time', 'flies'], possible_tags={0 : 'VB'})[0]
ScoredParse('(S1 (S (VP (VB Time) (NP (VBZ flies)))))', parser_score=-54.3497715 5750189, reranker_score=-16.681734375725263)

from bllip-parser.

Thanks. This is very helpful.

from bllip-parser.