When I was running the command python amr_parsing.py -m preprocess --amrfmt amr ./tmp.txt.all.basic-abt-brown-verb.parsed, something went wrong. What happened?
This is the content in tmp.txt.all.basic-abt-brown-verb.parsed file:
# ::id 1
# ::snt Whenever a reporter adverted to the new Nixon, the candidate bridled; he remembered that as an accusation of trickiness in previous campaigns and resented the question.
(x / xconcept
:x (x13 / and
:op15 (x1 / whenever)
:op2 (x12 / bridle
:concession (x4 / advert
:ARG0 (x3 / person
:ARG0-of (r / report-01))
:ARG2 (x8 / person
:name (n / name
:op1 "Nixon")
:mod (x7 / new)))
:ARG0 (x11 / candidate)
:ARG1 (x25 / and
:op1 (x15 / remember-01
:ARG0 (x14 / he)
:ARG1 (x19 / accusation
:beneficiary (x24 / campaign-01
:time (x23 / previous))))
:op2 (x26 / resent
:ARG0 x14
:ARG1 (x28 / question-01))))))
# ::id 2
# ::snt 30 For many in Capistrano, no welcome for swallows 22 REGIONAL/32-40 The oldest clinic in New York City, the Northern Dispensary at 165 Waverly Place, will close in May and become a nursing home for AIDS patients.
(x34 / and
:op1 (x31 / close-01
:null_edge (x23 / null_tag
:null_edge (x8 / welcome-01
:null_edge 30
:polarity -
:ARG1 regional/32
:null_edge 22)
:ARG1 (x16 / clinic
:domain (x10 / swallow-01)
:mod (x15 / old
:degree (m / most))
:location (x20 / city
:null_edge (x18 / null_tag)
:null_edge (x19 / country
:name (n3 / name
:op1 "York")))))
:location (x28 / country
:name (n / name
:op1 "Place")
:null_edge (x26 / 165)
:null_edge (x27 / country
:name (n1 / name
:op1 "Waverly"))))
:time (x33 / date-entity))
:op2 (x35 / become-01
:ARG2 (x38 / home
:purpose (x37 / nursing)
:location-of (x41 / patient
:mod (x40 / disease
:name (n2 / name
:op1 "AIDS"))))))
This is the result of the script and the error message:
Writing sentence file to ./tmp.txt.all.basic-abt-brown-verb.parsed.sent
Start Stanford CoreNLP...
java -Xmx2500m -cp stanfordnlp/stanford-corenlp-full-2015-04-20/stanford-corenlp-3.5.2.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/stanford-corenlp-3.5.2-models.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/joda-time.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/xom.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/jollyday.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/protobuf.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/javax.json.jar:stanfordnlp/stanford-corenlp-full-2015-04-20/ejml-0.23.jar edu.stanford.nlp.pipeline.StanfordCoreNLP -props stanfordnlp/default.properties
Loading Models: 4/4
Read token,lemma,name entity file ./tmp.txt.all.basic-abt-brown-verb.parsed.sent.prp...
========================================
'Whenever a reporter adverted to the new Nixon, the candidate bridled; he remembered that as an accusation of trickiness in previous campaigns and resented the question.\r\n\r\nSentence #1 (29 tokens):\r\nWhenever a reporter adverted to the new Nixon, the candidate bridled; he remembered that as an accusation of trickiness in previous campaigns and resented the question.\r\n[Text=Whenever CharacterOffsetBegin=0 CharacterOffsetEnd=8 PartOfSpeech=NNP Lemma=Whenever NamedEntityTag=O]\r\n[Text=a CharacterOffsetBegin=9 CharacterOffsetEnd=10 PartOfSpeech=DT Lemma=a NamedEntityTag=O]\r\n[Text=reporter CharacterOffsetBegin=11 CharacterOffsetEnd=19 PartOfSpeech=NN Lemma=reporter NamedEntityTag=O]\r\n[Text=adverted CharacterOffsetBegin=20 CharacterOffsetEnd=28 PartOfSpeech=VBN Lemma=advert NamedEntityTag=O]\r\n[Text=to CharacterOffsetBegin=29 CharacterOffsetEnd=31 PartOfSpeech=TO Lemma=to NamedEntityTag=O]\r\n[Text=the CharacterOffsetBegin=32 CharacterOffsetEnd=35 PartOfSpeech=DT Lemma=the NamedEntityTag=O]\r\n[Text=new CharacterOffsetBegin=36 CharacterOffsetEnd=39 PartOfSpeech=JJ Lemma=new NamedEntityTag=O]\r\n[Text=Nixon CharacterOffsetBegin=40 CharacterOffsetEnd=45 PartOfSpeech=NNP Lemma=Nixon NamedEntityTag=PERSON]\r\n[Text=, CharacterOffsetBegin=45 CharacterOffsetEnd=46 PartOfSpeech=, Lemma=, NamedEntityTag=O]\r\n[Text=the CharacterOffsetBegin=47 CharacterOffsetEnd=50 PartOfSpeech=DT Lemma=the NamedEntityTag=O]\r\n[Text=candidate CharacterOffsetBegin=51 CharacterOffsetEnd=60 PartOfSpeech=NN Lemma=candidate NamedEntityTag=O]\r\n[Text=bridled CharacterOffsetBegin=61 CharacterOffsetEnd=68 PartOfSpeech=VBD Lemma=bridle NamedEntityTag=O]\r\n[Text=; CharacterOffsetBegin=68 CharacterOffsetEnd=69 PartOfSpeech=: Lemma=; NamedEntityTag=O]\r\n[Text=he CharacterOffsetBegin=70 CharacterOffsetEnd=72 PartOfSpeech=PRP Lemma=he NamedEntityTag=O]\r\n[Text=remembered CharacterOffsetBegin=73 CharacterOffsetEnd=83 PartOfSpeech=VBD Lemma=remember NamedEntityTag=O]\r\n[Text=that CharacterOffsetBegin=84 CharacterOffsetEnd=88 PartOfSpeech=IN Lemma=that NamedEntityTag=O]\r\n[Text=as CharacterOffsetBegin=89 CharacterOffsetEnd=91 PartOfSpeech=IN Lemma=as NamedEntityTag=O]\r\n[Text=an CharacterOffsetBegin=92 CharacterOffsetEnd=94 PartOfSpeech=DT Lemma=a NamedEntityTag=O]\r\n[Text=accusation CharacterOffsetBegin=95 CharacterOffsetEnd=105 PartOfSpeech=NN Lemma=accusation NamedEntityTag=O]\r\n[Text=of CharacterOffsetBegin=106 CharacterOffsetEnd=108 PartOfSpeech=IN Lemma=of NamedEntityTag=O]\r\n[Text=trickiness CharacterOffsetBegin=109 CharacterOffsetEnd=119 PartOfSpeech=NN Lemma=trickiness NamedEntityTag=O]\r\n[Text=in CharacterOffsetBegin=120 CharacterOffsetEnd=122 PartOfSpeech=IN Lemma=in NamedEntityTag=O]\r\n[Text=previous CharacterOffsetBegin=123 CharacterOffsetEnd=131 PartOfSpeech=JJ Lemma=previous NamedEntityTag=O]\r\n[Text=campaigns CharacterOffsetBegin=132 CharacterOffsetEnd=141 PartOfSpeech=NNS Lemma=campaign NamedEntityTag=O]\r\n[Text=and CharacterOffsetBegin=142 CharacterOffsetEnd=145 PartOfSpeech=CC Lemma=and NamedEntityTag=O]\r\n[Text=resented CharacterOffsetBegin=146 CharacterOffsetEnd=154 PartOfSpeech=VBD Lemma=resent NamedEntityTag=O]\r\n[Text=the CharacterOffsetBegin=155 CharacterOffsetEnd=158 PartOfSpeech=DT Lemma=the NamedEntityTag=O]\r\n[Text=question CharacterOffsetBegin=159 CharacterOffsetEnd=167 PartOfSpeech=NN Lemma=question NamedEntityTag=O]\r\n[Text=. CharacterOffsetBegin=167 CharacterOffsetEnd=168 PartOfSpeech=. Lemma=. NamedEntityTag=O]\r\nNLP> '
========================================
'30 For many in Capistrano, no welcome for swallows 22 REGIONAL/32-40 The oldest clinic in New York City, the Northern Dispensary at 165 Waverly Place, will close in May and become a nursing home for AIDS patients.\r\n\r\nSentence #1 (42 tokens):\r\n30 For many in Capistrano, no welcome for swallows 22 REGIONAL/32-40 The oldest clinic in New York City, the Northern Dispensary at 165 Waverly Place, will close in May and become a nursing home for AIDS patients.\r\n[Text=30 CharacterOffsetBegin=0 CharacterOffsetEnd=2 PartOfSpeech=CD Lemma=30 NamedEntityTag=NUMBER NormalizedNamedEntityTag=30.0]\r\n[Text=For CharacterOffsetBegin=3 CharacterOffsetEnd=6 PartOfSpeech=IN Lemma=for NamedEntityTag=O]\r\n[Text=many CharacterOffsetBegin=7 CharacterOffsetEnd=11 PartOfSpeech=JJ Lemma=many NamedEntityTag=O]\r\n[Text=in CharacterOffsetBegin=12 CharacterOffsetEnd=14 PartOfSpeech=IN Lemma=in NamedEntityTag=O]\r\n[Text=Capistrano CharacterOffsetBegin=15 CharacterOffsetEnd=25 PartOfSpeech=NNP Lemma=Capistrano NamedEntityTag=LOCATION]\r\n[Text=, CharacterOffsetBegin=25 CharacterOffsetEnd=26 PartOfSpeech=, Lemma=, NamedEntityTag=O]\r\n[Text=no CharacterOffsetBegin=27 CharacterOffsetEnd=29 PartOfSpeech=DT Lemma=no NamedEntityTag=O]\r\n[Text=welcome CharacterOffsetBegin=30 CharacterOffsetEnd=37 PartOfSpeech=JJ Lemma=welcome NamedEntityTag=O]\r\n[Text=for CharacterOffsetBegin=38 CharacterOffsetEnd=41 PartOfSpeech=IN Lemma=for NamedEntityTag=O]\r\n[Text=swallows CharacterOffsetBegin=42 CharacterOffsetEnd=50 PartOfSpeech=NNS Lemma=swallow NamedEntityTag=O]\r\n[Text=22 CharacterOffsetBegin=51 CharacterOffsetEnd=53 PartOfSpeech=CD Lemma=22 NamedEntityTag=NUMBER NormalizedNamedEntityTag=22.0]\r\n[Text=REGIONAL/32 CharacterOffsetBegin=54 CharacterOffsetEnd=65 PartOfSpeech=NN Lemma=regional/32 NamedEntityTag=O]\r\n[Text=-40 CharacterOffsetBegin=65 CharacterOffsetEnd=68 PartOfSpeech=CD Lemma=-40 NamedEntityTag=NUMBER NormalizedNamedEntityTag=-40.0]\r\n[Text=The CharacterOffsetBegin=69 CharacterOffsetEnd=72 PartOfSpeech=DT Lemma=the NamedEntityTag=O]\r\n[Text=oldest CharacterOffsetBegin=73 CharacterOffsetEnd=79 PartOfSpeech=JJS Lemma=oldest NamedEntityTag=O]\r\n[Text=clinic CharacterOffsetBegin=80 CharacterOffsetEnd=86 PartOfSpeech=NN Lemma=clinic NamedEntityTag=O]\r\n[Text=in CharacterOffsetBegin=87 CharacterOffsetEnd=89 PartOfSpeech=IN Lemma=in NamedEntityTag=O]\r\n[Text=New CharacterOffsetBegin=90 CharacterOffsetEnd=93 PartOfSpeech=NNP Lemma=New NamedEntityTag=LOCATION]\r\n[Text=York CharacterOffsetBegin=94 CharacterOffsetEnd=98 PartOfSpeech=NNP Lemma=York NamedEntityTag=LOCATION]\r\n[Text=City CharacterOffsetBegin=99 CharacterOffsetEnd=103 PartOfSpeech=NNP Lemma=City NamedEntityTag=LOCATION]\r\n[Text=, CharacterOffsetBegin=103 CharacterOffsetEnd=104 PartOfSpeech=, Lemma=, NamedEntityTag=O]\r\n[Text=the CharacterOffsetBegin=105 CharacterOffsetEnd=108 PartOfSpeech=DT Lemma=the NamedEntityTag=O]\r\n[Text=Northern CharacterOffsetBegin=109 CharacterOffsetEnd=117 PartOfSpeech=NNP Lemma=Northern NamedEntityTag=O]\r\n[Text=Dispensary CharacterOffsetBegin=118 CharacterOffsetEnd=128 PartOfSpeech=NNP Lemma=Dispensary NamedEntityTag=O]\r\n[Text=at CharacterOffsetBegin=129 CharacterOffsetEnd=131 PartOfSpeech=IN Lemma=at NamedEntityTag=O]\r\n[Text=165 CharacterOffsetBegin=132 CharacterOffsetEnd=135 PartOfSpeech=CD Lemma=165 NamedEntityTag=NUMBER NormalizedNamedEntityTag=165.0]\r\n[Text=Waverly CharacterOffsetBegin=136 CharacterOffsetEnd=143 PartOfSpeech=NNP Lemma=Waverly NamedEntityTag=LOCATION]\r\n[Text=Place CharacterOffsetBegin=144 CharacterOffsetEnd=149 PartOfSpeech=NNP Lemma=Place NamedEntityTag=LOCATION]\r\n[Text=, CharacterOffsetBegin=149 CharacterOffsetEnd=150 PartOfSpeech=, Lemma=, NamedEntityTag=O]\r\n[Text=will CharacterOffsetBegin=151 CharacterOffsetEnd=155 PartOfSpeech=MD Lemma=will NamedEntityTag=O]\r\n[Text=close CharacterOffsetBegin=156 CharacterOffsetEnd=161 PartOfSpeech=VB Lemma=close NamedEntityTag=O]\r\n[Text=in CharacterOffsetBegin=162 CharacterOffsetEnd=164 PartOfSpeech=IN Lemma=in NamedEntityTag=O]\r\n[Text=May CharacterOffsetBegin=165 CharacterOffsetEnd=168 PartOfSpeech=NNP Lemma=May NamedEntityTag=DATE NormalizedNamedEntityTag=XXXX-05 Timex=<TIMEX3 tid="t1" type="DATE" value="XXXX-05">May</TIMEX3>]\r\n[Text=and CharacterOffsetBegin=169 CharacterOffsetEnd=172 PartOfSpeech=CC Lemma=and NamedEntityTag=O]\r\n[Text=become CharacterOffsetBegin=173 CharacterOffsetEnd=179 PartOfSpeech=VB Lemma=become NamedEntityTag=O]\r\n[Text=a CharacterOffsetBegin=180 CharacterOffsetEnd=181 PartOfSpeech=DT Lemma=a NamedEntityTag=O]\r\n[Text=nursing CharacterOffsetBegin=182 CharacterOffsetEnd=189 PartOfSpeech=NN Lemma=nursing NamedEntityTag=O]\r\n[Text=home CharacterOffsetBegin=190 CharacterOffsetEnd=194 PartOfSpeech=NN Lemma=home NamedEntityTag=O]\r\n[Text=for CharacterOffsetBegin=195 CharacterOffsetEnd=198 PartOfSpeech=IN Lemma=for NamedEntityTag=O]\r\n[Text=AIDS CharacterOffsetBegin=199 CharacterOffsetEnd=203 PartOfSpeech=NN Lemma=aid NamedEntityTag=MISC]\r\n[Text=patients CharacterOffsetBegin=204 CharacterOffsetEnd=212 PartOfSpeech=NNS Lemma=patient NamedEntityTag=O]\r\n[Text=. CharacterOffsetBegin=212 CharacterOffsetEnd=213 PartOfSpeech=. Lemma=. NamedEntityTag=O]\r\nNLP> NLP> '
Traceback (most recent call last):
File "amr_parsing.py", line 436, in <module>
main()
File "amr_parsing.py", line 169, in main
instances = preprocess(amr_file,START_SNLP=True,INPUT_AMR=args.amrfmt, PRP_FORMAT=args.prpfmt)
File "/home/xx/camr/preprocessing.py", line 377, in preprocess
amr = AMR.parse_string(amr_strings[i])
File "/home/xx/camr/common/AMRGraph.py", line 143, in parse_string
else: raise ParserError, "Unexpected token %s"%(token)
common.AMRGraph.ParserError: Unexpected token :op2
When I was running the command
python amr_parsing.py -m preprocess --amrfmt amr ./tmp.txt.all.basic-abt-brown-verb.parsed, something went wrong. What happened?This is the content in
tmp.txt.all.basic-abt-brown-verb.parsedfile:This is the result of the script and the error message: