Do the POS tags in the ACE-parsed ERG treebanks come from a model trained a while back with the TnT tagger?
I found this in the docs, but no details:
Batch Parsing
With sensible limits and using tnt for POS tagging (which enables unknown word processing).
I just need to know the provenance of the tags, wether they are gold or automatically predicted (I am assuming the latter).
I am talking about things like this (PRP, VBT, etc.), stored in particular in pydelphin’s Response objects:
(1, 0, 1, <0:1>, 1, "I", 0, "null", "PRP" 1.0) (2, 1, 2, <2:7>, 1, "agree", 0, "null", "VBP" 1.0) (3, 2, 3, <8:12>, 1, "with", 0, "null", "IN" 1.0) (4, 3, 4, <13:17>, 1, "most", 0, "null", "RBS" 1.0) (5, 4, 5, <18:20>, 1, "of", 0, "null", "IN" 1.0) (6, 5, 6, <21:24>, 1, "the", 0, "null", "DT" 1.0) (7, 6, 7, <25:31>, 1, "things", 0, "null", "NNS" 1.0) (8, 7, 8, <32:36>, 1, "that", 0, "null", "IN" 1.0) (9, 8, 9, <37:41>, 1, "your", 0, "null", "PRP$" 1.0) (10, 9, 10, <42:48>, 1, "father", 0, "null", "NN" 1.0) (11, 10, 11, <49:52>, 1, "was", 0, "null", "VBD" 1.0) (12, 11, 12, <53:59>, 1, "saying", 0, "null", "VBG" 1.0) (13, 12, 13, <59:60>, 1, ".", 0, "null", "." 1.0)