Closed bonsonsm closed 8 years ago
PyStanfordDependencies isn't a parser (just a way of converting trees to dependencies) so I'm confused how you got the second tree. Can you say more about the code you're running?
Hello,
I understand. It is not an issue with the package. The parser output is different. Kindly close this case.
I am using the following parser: parser = stanford.StanfordParser(model_path=".\edu\stanford\nlp\models\lexparser\englishPCFG.ser.gz")
objSentences = parser.raw_parse_sents(strSentenceList)
I tried two other parsers as well:
But not getting the required output matching the initial on. Kindly let me know if you have any insights on how to proceed with this.
Thanks and Regards, Bonson
Sorry, I'm still not sure which Python package you're using to get your trees. Either way, I'm afraid this isn't the right forum for this issue -- please file this issue with the package that stanford.StanfordParser
is from (nltk.parse.stanford
maybe? In this case, you should head over to NLTK). Hope this helps.
Hello,
The sample sentence I used is: "Janet had prune juice today before lunch." When I use StanfordCoreNLP in R and run it I get the result:
(ROOT (S (NP (NNP Janet)) (VP (VBD had) (S (VP (VB prune) (NP (NN juice)) (NP-TMP (NN today)) (PP (IN before) (NP (NN lunch)))))) (. .)))
Using pyStanfordDependencies, I get:
(S (NP (NNP Janet)) (VP (VBD had) (VP (VBN prune) (NP (NN juice) (NN today)) (PP (IN before) (NP (NN lunch))))) (. .))
This difference makes it difficult to apply rules to get triples from the sentence. Kindly review. Maybe I am making a mistake somewhere.
Regards, Bonson