Comments (5)
I've been able to demonstrate this using your stock English model.
As well as for complex voice emotional recognition for emotions not included in Mind Reading .
1 As as RB _ 3 advmod _ @#r$%
2 well well RB _ 3 advmod _ @#r$%
3 as as IN _ 5 advmod _ @#r$%
4 for for IN _ 0 conj _ @#r$%
5 complex complex JJ _ 8 nmod _ @#r$%
6 voice voice NN _ 8 nmod _ @#r$%
7 emotional emotional JJ _ 8 nmod _ @#r$%
8 recognition recognition NN _ 4 pobj _ @#r$%
9 for for IN _ 8 prep _ @#r$%
10 emotions emotion NNS _ 9 pobj _ @#r$%
11 not not RB _ 12 neg _ @#r$%
12 included include VBN pos2=VBD 0 root _ @#r$%
13 in in IN _ 12 prep _ @#r$%
14 Mind mind NN pos2=NNP 15 compound _ @#r$%
15 Reading reading NN pos2=VBG 13 pobj _ @#r$%
16 . . . _ 12 punct _ @#r$%
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I tried adding a feature to the model.
Please don't laugh if my attempt to figure out the feature templates was unsuccessful.
My idea was to discourage things like a conj deprel with the root. Of course, this sort of thing can't globally ding sentences for having more than one root. If there's a way to introduce that idea into the feature set I haven't understood it yet.
<feature f0="i:dependency_label" f1="i_h:part_of_speech_tag"/>
With my universal training (UD treebank + converted PTB) and the UD dev set the accuracy was the same,
UAS 0.88 LAS 0.85 total tokens 25148
but the number of two-headed outputs from the UD dev set dropped from 4% to 3%.
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We somewhat belatedly read the papers and understand that this is expected, so we thinking about how to cope.
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Sorry for the late reply; I was meeting a grant proposal deadline. Multiple roots may be caused because by headless nodes; when the parser doesn't find any head, then it by default connects it to the root to keep the entire tree connected, but this is something I should retouch. I'm planning to adapt our structure to UD more now, so I can experiment this more myself as well.
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OK, thanks.
On Thu, Jul 21, 2016 at 2:33 PM, Jinho D. Choi [email protected]
wrote:
Sorry for the late reply; I was meeting a grant proposal deadline.
Multiple roots may be caused because by headless nodes; when the parser
doesn't find any head, then it by default connects it to the root to keep
the entire tree connected, but this is something I should retouch. I'm
planning to adapt our structure to UD more now, so I can experiment this
more myself as well.—
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Related Issues (20)
- Part-of-Speech Tagging example HOT 1
- only POS tagger HOT 4
- ArrayIndexOutOfBoundException in NER Training HOT 4
- Adding new values to Named Entity. HOT 5
- StringIndexOutOfBoundsException HOT 1
- How do you use the POS tagger? HOT 2
- Are components reentrant? Can components be cloned? HOT 2
- Does the dependency parser 'depend' on the named entity tagger? HOT 1
- Garbage tokens? HOT 2
- Dep parser appears to produce multiple nodes with the head of the tree as the root. HOT 1
- Universal Dependencies HOT 10
- CLI for Eval? HOT 2
- Infinite recursion in AbstractNLPDecoder.createTSVReader() HOT 2
- slf4j would be more flexible than raw log4j HOT 6
- POS tagger model takes time to load HOT 2
- Exception reading dependency model HOT 1
- How to speed up the dependency parser by reworking one method HOT 2
- tsv option not working HOT 1
- Nlp Training for NER HOT 1
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