AngledLuffa
commented
10 years ago What happens if you leave out some of the annotators? Does it work then?
On Wed, Mar 12, 2014 at 10:54 AM, scamosa notifications@github.com wrote:
I have installed the entire Stanford library on Eclipse. When I run the following source code, the program just crashes, with the last message being "Adding annotator sentiment". It remains like without any tree or any output stating positive/negative/neutral. Kindly can anyone help me out?
SOURCE CODE:
import edu.stanford.nlp.dcoref.CorefChain; import edu.stanford.nlp.dcoref.CorefCoreAnnotations.CorefChainAnnotation; import edu.stanford.nlp.ling.CoreAnnotations.NamedEntityTagAnnotation; import edu.stanford.nlp.ling.CoreAnnotations.PartOfSpeechAnnotation; import edu.stanford.nlp.ling.CoreAnnotations.SentencesAnnotation; import edu.stanford.nlp.ling.CoreAnnotations.TextAnnotation; import edu.stanford.nlp.ling.CoreAnnotations.TokensAnnotation; import edu.stanford.nlp.ling.CoreLabel; import edu.stanford.nlp.pipeline.Annotation; import edu.stanford.nlp.pipeline.StanfordCoreNLP; import edu.stanford.nlp.semgraph.SemanticGraph; import edu.stanford.nlp.semgraph.SemanticGraphCoreAnnotations.CollapsedCCProcessedDependenciesAnnotation; import edu.stanford.nlp.trees.Tree; import edu.stanford.nlp.trees.TreeCoreAnnotations.TreeAnnotation; import edu.stanford.nlp.util.CoreMap; import java.io.IOException; import java.util.List; import java.util.Map; import java.util.Properties;
public class TagText { public static void main(String[] args) throws IOException, ClassNotFoundException { // creates a StanfordCoreNLP object, with POS tagging, lemmatization, NER, parsing, and coreference resolution Properties props = new Properties(); props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, sentiment"); StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
// read some text in the text variable String text = "European Stocks Drop as Maersk, Valeo Fall on Stake Sales"; // create an empty Annotation just with the given text Annotation document = new Annotation(text); // run all Annotators on this text pipeline.annotate(document); // these are all the sentences in this document // a CoreMap is essentially a Map that uses class objects as keys and has values with custom types List<CoreMap> sentences = document.get(SentencesAnnotation.class); for(CoreMap sentence: sentences) { // traversing the words in the current sentence // a CoreLabel is a CoreMap with additional token-specific methods for (CoreLabel token: sentence.get(TokensAnnotation.class)) { // this is the text of the token String word = token.get(TextAnnotation.class); // this is the POS tag of the token String pos = token.get(PartOfSpeechAnnotation.class); // this is the NER label of the token String ne = token.get(NamedEntityTagAnnotation.class); } // this is the parse tree of the current sentence Tree tree = sentence.get(TreeAnnotation.class); // this is the Stanford dependency graph of the current sentence SemanticGraph dependencies = sentence.get(CollapsedCCProcessedDependenciesAnnotation.class); } // This is the coreference link graph // Each chain stores a set of mentions that link to each other, // along with a method for getting the most representative mention // Both sentence and token offsets start at 1! Map<Integer, CorefChain> graph = document.get(CorefChainAnnotation.class);} }
THE FOLLOWING MESSAGES APPEAR ON THE ECLIPSE CONSOLE with no tree or any output stating positive/negative/neutral:
Adding annotator tokenize Adding annotator ssplit Adding annotator pos Reading POS tagger model from edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger ... done [4.0 sec]. Adding annotator lemma Adding annotator ner Loading classifier from edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz ... done [13.5 sec]. Loading classifier from edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf.ser.gz ... done [11.2 sec]. Loading classifier from edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz ... done [9.4 sec]. Reading TokensRegex rules from edu/stanford/nlp/models/sutime/defs.sutime.txt Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.sutime.txt Mar 12, 2014 6:33:22 PM edu.stanford.nlp.ling.tokensregex.CoreMapExpressionExtractor appendRules INFO: Ignoring inactive rule: null Mar 12, 2014 6:33:22 PM edu.stanford.nlp.ling.tokensregex.CoreMapExpressionExtractor appendRules INFO: Ignoring inactive rule: temporal-composite-8:ranges Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.holidays.sutime.txt Initializing JollyDayHoliday for sutime with classpath:edu/stanford/nlp/models/sutime/jollyday/Holidays_sutime.xml Reading TokensRegex rules from edu/stanford/nlp/models/sutime/defs.sutime.txt Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.sutime.txt Mar 12, 2014 6:33:23 PM edu.stanford.nlp.ling.tokensregex.CoreMapExpressionExtractor appendRules INFO: Ignoring inactive rule: null Mar 12, 2014 6:33:23 PM edu.stanford.nlp.ling.tokensregex.CoreMapExpressionExtractor appendRules INFO: Ignoring inactive rule: temporal-composite-8:ranges Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.holidays.sutime.txt Adding annotator parse Loading parser from serialized file edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz ... done [2.8 sec]. Adding annotator sentiment
Reply to this email directly or view it on GitHubhttps://github.com/stanfordnlp/CoreNLP/issues/19 .
scamosa
I have installed the entire Stanford library on Eclipse. When I run the following source code, the program just crashes, with the last message being "Adding annotator sentiment". It remains like without any tree or any output stating positive/negative/neutral. Kindly can anyone help me out?
SOURCE CODE:
THE FOLLOWING MESSAGES APPEAR ON THE ECLIPSE CONSOLE with no tree or any output stating positive/negative/neutral: