stanford-nlp

问题 I'm using StanfordNLP in order to classify some text. It works fine when I use train files with a maximum of 160K lines. But, if I use larger ones, I receive a java.lang.OutOfMemoryError: Java heap space . I'm using the following properties: e.s.n.c.ColumnDataClassifier - Setting ColumnDataClassifier properties e.s.n.c.ColumnDataClassifier - 1.useAllSplitWordTriples = true e.s.n.c.ColumnDataClassifier - useQN = true e.s.n.c.ColumnDataClassifier - encoding = utf-8 e.s.n.c.ColumnDataClassifier

问题 Stanford NLP postagger claims imperative verbs added to recent version. I've inputted lots of text with abundant and obvious imperatives, but there seems to be no tag for them on output. Must one, after all, train it for this pos? 回答1: There is no special tag for imperatives, they are simply tagged as VB . The info on the website refers to the fact that we added a bunch of manually annotated imperative sentences to our training data such that the POS tagger gets more of them right, i.e. tags

问题 we are trying to implement name entity recognition on millions of comments/feedback and the process appears to be slow. We are thinking of removing stop words/frequent words from the texts and apply ner on them. Does removing stop words affect the accuracy of ner? 回答1: I think it's plausible you will get respectable F1 scores if you run on a sentence with the stop words removed. Ultimately you will have to experiment with it and see if the quality is acceptable for your needs. 来源： https:/

问题 If PCFG is like, NP -> ADJ N [0.6] NP -> N [0.4] N -> cat [0.2] N -> dog [0.8] What will be CNF form? Will it be the following? NP -> ADJ NP [0.6] NP -> cat [0.08] NP -> dog [0.32] or somethings else? 回答1: NP -> ADJ NP [0.6] NP -> cat [0.08] NP -> dog [0.32] Your answer is correct because you need to get the same probability for the result by applying both the original and the converted set of rules (in CNF). 来源： https://stackoverflow.com/questions/39769119/what-will-be-cnf-form-of-this

问题 if you run: java -mx3g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -props StanfordCoreNLP-spanish.properties java -mx3g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLP -props StanfordCoreNLP-spanish.properties The second command open a terminal and Spanish parser works fine, but from the Server version it use the English parser and not the Spanish. ~/CoreNLP/stanford-corenlp-full-2015-12-09# java -mx3g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -props

问题 When I'm trying to print the tree of a sentence I've parsed using the RNN parser, it crashes when there is a MWE dependency in the sentence. It crashes with the latest version of the Stanford NLP (3.5.2), but not with the previous one (3.5.1). Here is the error I get: java.lang.IllegalArgumentException: No head rule defined for MWE using class edu.stanford.nlp.trees.SemanticHeadFinder in (MWE (VBG according) (TO to)) at edu.stanford.nlp.trees.AbstractCollinsHeadFinder.determineNonTrivialHead

问题 I'm trying to create a distant supervision corpus. Thus far I've assembled the data, and passed it through an NER system, so you can see an example below. Original data: <p> Myles Brand, the president of the National Collegiate Athletic Association, said in a telephone interview that he had not been approached about whether the N.C.A.A. might oversee a panel for the major bowl games similar to the one that chooses teams for the men's and women's basketball tournaments. </p> Processed with

问题 I am trying to use the coreNLP package. I ran the following commands and encounter the GC overhead limit exceeded error. library(rJava) downloadCoreNLP() initCoreNLP() Error is like this : Loading classifier from edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz ... Error in rJava::.jnew("edu.stanford.nlp.pipeline.StanfordCoreNLP", basename(path)) : java.lang.OutOfMemoryError: GC overhead limit exceeded Error during wrapup: cannot open the connection I don't know much of

问题 I am trying to run simple program available on this website https://stanfordnlp.github.io/CoreNLP/api.html My Program import java.io.BufferedReader; import java.io.BufferedWriter; import java.io.FileNotFoundException; import java.io.FileReader; import java.io.FileWriter; import java.io.IOException; import java.io.PrintWriter; import java.util.List; import java.util.Properties; import edu.stanford.nlp.ling.CoreAnnotations.NamedEntityTagAnnotation; import edu.stanford.nlp.ling.CoreAnnotations

问题 I want to use Stanford CoreNLP Parser to parse a sentence with the flag "makeCopulaHead" activated. In my file input.txt, I have the following sentence: I am tall. The objective is to not have a copula relation (cop) in the output dependency tree. I tried: java -cp "*" -mx8g edu.stanford.nlp.pipeline.StanfordCoreNLP -makeCopulaHead -file input.txt The .xml file contains cop relation :( I also tried (a bug with xml-output: https://mailman.stanford.edu/pipermail/java-nlp-user/2013-January