public static void clearPredictions(Data data) { for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector sentence : sentences) { for (int i = 0; i < sentence.size(); i++) { ((NEWord) sentence.get(i)).neTypeLevel1 = null; ((NEWord) sentence.get(i)).neTypeLevel2 = null; } } } } }
public static void clearPredictions(Data data) { for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector sentence : sentences) { for (int i = 0; i < sentence.size(); i++) { ((NEWord) sentence.get(i)).neTypeLevel1 = null; ((NEWord) sentence.get(i)).neTypeLevel2 = null; } } } } }
public static void clearPredictions(Data data) { for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector sentence : sentences) { for (int i = 0; i < sentence.size(); i++) { ((NEWord) sentence.get(i)).neTypeLevel1 = null; ((NEWord) sentence.get(i)).neTypeLevel2 = null; } } } } }
/** * Adds the specified child to the end of the vector, informing the child of its parent and * index and linking the child to its only neighbor (which was previously the last child in the * vector). * * @param c The child to add. **/ public boolean add(LinkedChild c) { c.parent = this; if (children.size() > 0) { LinkedChild p = get(children.size() - 1); p.next = c; c.previous = p; } return children.add(c); }
/** * Retrieves the next sentence from the files being parsed. * * @return A <code>LinkedVector</code> representation of the next sentence. **/ public Object next() { if (currentWord == null) { LinkedVector vector = (LinkedVector) super.next(); if (vector != null) currentWord = (Word) vector.get(0); } Word result = currentWord; if (currentWord != null) currentWord = (Word) currentWord.next; return result; } }
/** * Retrieves the next sentence from the files being parsed. * * @return A <code>LinkedVector</code> representation of the next sentence. **/ public Object next() { if (currentWord == null) { LinkedVector vector = (LinkedVector) super.next(); if (vector != null) currentWord = (Word) vector.get(0); } Word result = currentWord; if (currentWord != null) currentWord = (Word) currentWord.next; return result; } }
/** * Returns the next <code>LinkedChild</code> parsed. * * @return The next <code>LinkedChild</code> parsed, or <code>null</code> if there are no more * children in the stream. **/ public Object next() { while (next == null) { LinkedVector v = (LinkedVector) parser.next(); if (v == null) return null; next = v.get(0); } LinkedChild result = next; next = next.next; return result; }
public static void setLevel1AggregationFeatures(Data data, boolean useGoldData) { logger.debug("Extracting features for level 2 inference"); for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector twords : sentences) { for (int j = 0; j < twords.size(); j++) { setLevel1AggregationFeatures((NEWord) twords.get(j), useGoldData); } } } logger.debug("Done - Extracting features for level 2 inference"); }
public static void setLevel1AggregationFeatures(Data data, boolean useGoldData) { logger.debug("Extracting features for level 2 inference"); for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector twords : sentences) { for (int j = 0; j < twords.size(); j++) { setLevel1AggregationFeatures((NEWord) twords.get(j), useGoldData); } } } logger.debug("Done - Extracting features for level 2 inference"); }
public static void setLevel1AggregationFeatures(Data data, boolean useGoldData) { logger.debug("Extracting features for level 2 inference"); for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector twords : sentences) { for (int j = 0; j < twords.size(); j++) { setLevel1AggregationFeatures((NEWord) twords.get(j), useGoldData); } } } logger.debug("Done - Extracting features for level 2 inference"); }
public static void write(Data data, String outFile) { OutFile out = new OutFile(outFile); for (int did = 0; did < data.documents.size(); did++) { for (int i = 0; i < data.documents.get(did).sentences.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.documents.get(did).sentences.get(i).size(); j++) buf.append(((NEWord) data.documents.get(did).sentences.get(i).get(j)).form) .append(" "); out.println(buf.toString()); } } out.close(); }
public static void write(Data data, String outFile) { OutFile out = new OutFile(outFile); for (int did = 0; did < data.documents.size(); did++) { for (int i = 0; i < data.documents.get(did).sentences.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.documents.get(did).sentences.get(i).size(); j++) buf.append(((NEWord) data.documents.get(did).sentences.get(i).get(j)).form) .append(" "); out.println(buf.toString()); } } out.close(); }
public static void write(Data data, String outFile) { OutFile out = new OutFile(outFile); for (int did = 0; did < data.documents.size(); did++) { for (int i = 0; i < data.documents.get(did).sentences.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.documents.get(did).sentences.get(i).size(); j++) buf.append(((NEWord) data.documents.get(did).sentences.get(i).get(j)).form) .append(" "); out.println(buf.toString()); } } out.close(); }
public static void write(Vector<LinkedVector> data, String outFile) { OutFile out = new OutFile(outFile); for (int i = 0; i < data.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.elementAt(i).size(); j++) buf.append(((NEWord) data.elementAt(i).get(j)).form).append(" "); out.println(buf.toString()); } out.close(); } }
public static void write(Vector<LinkedVector> data, String outFile) { OutFile out = new OutFile(outFile); for (int i = 0; i < data.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.elementAt(i).size(); j++) buf.append(((NEWord) data.elementAt(i).get(j)).form).append(" "); out.println(buf.toString()); } out.close(); } }
public static void write(Vector<LinkedVector> data, String outFile) { OutFile out = new OutFile(outFile); for (int i = 0; i < data.size(); i++) { StringBuilder buf = new StringBuilder(2000); for (int j = 0; j < data.elementAt(i).size(); j++) buf.append(((NEWord) data.elementAt(i).get(j)).form).append(" "); out.println(buf.toString()); } out.close(); } }
public static String showSentenceVector(Vector<LinkedVector> sentences) { String display = ""; for (LinkedVector v : sentences) { for (int i = 0; i < v.size(); ++i) { NEWord s = (NEWord) (v.get(i)); display += (s.toString()); } } return display; }
public static String showSentenceVector(Vector<LinkedVector> sentences) { String display = ""; for (LinkedVector v : sentences) { for (int i = 0; i < v.size(); ++i) { NEWord s = (NEWord) (v.get(i)); display += (s.toString()); } } return display; }
public static String showSentenceVector(Vector<LinkedVector> sentences) { String display = ""; for (LinkedVector v : sentences) { for (int i = 0; i < v.size(); ++i) { NEWord s = (NEWord) (v.get(i)); display += (s.toString()); } } return display; }
private static void Bilou2Bio(Data data, LabelToLookAt labelType) { for (int docid = 0; docid < data.documents.size(); docid++) { ArrayList<LinkedVector> sentences = data.documents.get(docid).sentences; for (LinkedVector v : sentences) { for (int j = 0; j < v.size(); j++) { NEWord w = (NEWord) v.get(j); String label = w.getPrediction(labelType); if (!label.equalsIgnoreCase("O")) { if (w.getPrediction(labelType).startsWith("U-")) w.setPrediction("B-" + label.substring(2), labelType); if (w.getPrediction(labelType).startsWith("L-")) w.setPrediction("I-" + label.substring(2), labelType); } } } } }