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Update the CoNLLUReader test to read from the actual AnCora UD sentences, using expected gold values instead of reparsed values as the gold. This will let us test reading things the pipeline doesn't produce (such as UPOS vs XPOS or an enchanced graph) once those features are added
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‎data/edu/stanford/nlp/pipeline/es-example.conllu‎

Lines changed: 28 additions & 28 deletions
Original file line numberDiff line numberDiff line change
@@ -1,35 +1,35 @@
1-
# sent_id = dev-s48
1+
# sent_id = 3LB-CAST-a22-0-s10
22
# text = Pero la existencia de dos recién nacidos en la misma caja sólo podía deberse a un descuido de fábrica.
33
# orig_file_sentence 001#48
4-
1 Pero pero CCONJ CCONJ _ 14 advmod _ _
5-
2 la la DET DET Definite=Def|Gender=Fem|Number=Sing|PronType=Art 3 det _ _
6-
3 existencia existencia NOUN NOUN Gender=Fem|Number=Sing 14 nsubj _ _
7-
4 de de ADP ADP AdpType=Prep 5 case _ _
8-
5 dos dos NUM NUM Number=Plur|NumType=Card 3 nummod _ _
9-
6 recién recién ADV ADV _ 7 advmod _ _
10-
7 nacidos nacidos ADJ ADJ Gender=Masc|Number=Plur|VerbForm=Part 5 amod _ _
11-
8 en en ADP ADP AdpType=Prep 11 case _ _
12-
9 la la DET DET Definite=Def|Gender=Fem|Number=Sing|PronType=Art 11 det _ _
13-
10 misma misma DET DET Gender=Fem|Number=Sing|PronType=Ind 9 det _ _
14-
11 caja caja NOUN NOUN Gender=Fem|Number=Sing 3 nmod _ _
15-
12 sólo sólo ADV ADV _ 14 advmod _ _
16-
13 podía podía AUX AUX Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin 14 aux _ _
4+
1 Pero pero CCONJ cc _ 14 advmod 14:advmod _
5+
2 la el DET da0fs0 Definite=Def|Gender=Fem|Number=Sing|PronType=Art 3 det 3:det _
6+
3 existencia existencia NOUN ncfs000 Gender=Fem|Number=Sing 14 nsubj 14:nsubj ArgTem=arg1:tem
7+
4 de de ADP sps00 _ 7 case 7:case _
8+
5 dos dos NUM dn0cp0 Number=Plur|NumForm=Word|NumType=Card 7 nummod 7:nummod _
9+
6 recién recién ADV rg _ 7 advmod 7:advmod ArgTem=argM:tmp
10+
7 nacidos nacido ADJ aq0mpp Gender=Masc|Number=Plur|VerbForm=Part 3 amod 3:amod ArgTem=arg1:tem
11+
8 en en ADP sps00 _ 11 case 11:case _
12+
9 la el DET da0fs0 Definite=Def|Gender=Fem|Number=Sing|PronType=Art 11 det 11:det _
13+
10 misma mismo DET di0fs0 Gender=Fem|Number=Sing|PronType=Dem 9 det 9:det _
14+
11 caja caja NOUN ncfs000 Gender=Fem|Number=Sing 3 nmod 3:nmod ArgTem=argM:loc
15+
12 sólo sólo ADV rg _ 14 advmod 14:advmod ArgTem=argM:adv
16+
13 podía poder AUX vmii3s0 Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin 14 aux 14:aux _
1717
14-15 deberse _ _ _ _ _ _ _ _
18-
14 deber deber VERB VERB VerbForm=Inf 0 root _ _
19-
15 se se PRON PRON Person=3 14 obj _ _
20-
16 a a ADP ADP AdpType=Prep 18 case _ _
21-
17 un un DET DET Definite=Ind|Gender=Masc|Number=Sing|PronType=Art 18 det _ _
22-
18 descuido descuido NOUN NOUN Gender=Masc|Number=Sing 14 obj _ _
23-
19 de de ADP ADP AdpType=Prep 20 case _ _
24-
20 fábrica fábrica NOUN NOUN Gender=Fem|Number=Sing 18 nmod _ SpaceAfter=No
25-
21 . . PUNCT PUNCT PunctType=Peri 14 punct _ _
18+
14 deber deber VERB vmn0000 VerbForm=Inf 0 root 0:root _
19+
15 se él PRON _ Case=Acc|Person=3|PrepCase=Npr|PronType=Prs|Reflex=Yes 14 expl:pv 14:expl:pv _
20+
16 a a ADP sps00 _ 18 case 18:case _
21+
17 un uno DET di0ms0 Definite=Ind|Gender=Masc|Number=Sing|PronType=Art 18 det 18:det _
22+
18 descuido descuido NOUN ncms000 Gender=Masc|Number=Sing 14 obl:arg 14:obl:arg ArgTem=arg2:atr
23+
19 de de ADP sps00 _ 20 case 20:case _
24+
20 fábrica fábrica NOUN ncfs000 Gender=Fem|Number=Sing 18 nmod 18:nmod SpaceAfter=No|ArgTem=arg0:agt
25+
21 . . PUNCT fp PunctType=Peri 14 punct 14:punct _
2626

27-
# sent_id = dev-s49
27+
# sent_id = 3LB-CAST-a22-0-s11
2828
# text = De allí las rebajas.
2929
# orig_file_sentence 001#49
30-
1 De de ADP ADP AdpType=Prep 2 case _ _
31-
2 allí allí ADV ADV _ 4 advmod _ _
32-
3 las las DET DET Definite=Def|Gender=Fem|Number=Plur|PronType=Art 4 det _ _
33-
4 rebajas rebajas NOUN NOUN Gender=Fem|Number=Plur 0 root _ SpaceAfter=No
34-
5 . . PUNCT PUNCT PunctType=Peri 4 punct _ _
30+
1 De de ADP sps00 _ 2 case 2:case _
31+
2 allí allí ADV rg _ 4 advmod 4:advmod _
32+
3 las el DET da0fp0 Definite=Def|Gender=Fem|Number=Plur|PronType=Art 4 det 4:det _
33+
4 rebajas rebaja NOUN ncfp000 Gender=Fem|Number=Plur 0 root 0:root SpaceAfter=No
34+
5 . . PUNCT fp PunctType=Peri 4 punct 4:punct _
3535

‎itest/src/edu/stanford/nlp/pipeline/CoNLLUReaderITest.java‎

Lines changed: 271 additions & 41 deletions
Original file line numberDiff line numberDiff line change
@@ -5,8 +5,13 @@
55
import edu.stanford.nlp.util.*;
66

77
import static org.junit.Assert.assertEquals;
8+
import static org.junit.Assert.assertFalse;
9+
import static org.junit.Assert.assertNotNull;
10+
import static org.junit.Assert.assertTrue;
811

912
import java.io.*;
13+
import java.util.ArrayList;
14+
import java.util.List;
1015
import java.util.Properties;
1116

1217
import org.junit.Before;
@@ -24,53 +29,278 @@ public class CoNLLUReaderITest {
2429
public Annotation goldDocument;
2530
public Annotation readInDocument;
2631

27-
@Before
28-
public void setUp() throws IOException {
29-
// set up the pipeline
30-
Properties props = LanguageInfo.getLanguageProperties("spanish");
31-
props.put("annotators", "tokenize,ssplit,mwt,pos,lemma,depparse");
32-
pipeline = new StanfordCoreNLP(props);
33-
}
32+
static final String[] EXPECTED_SENTENCE_TEXT = {
33+
"Pero la existencia de dos recién nacidos en la misma caja sólo podía deberse a un descuido de fábrica.",
34+
"De allí las rebajas."
35+
};
36+
static final String EXPECTED_TEXT = String.join(System.lineSeparator(), EXPECTED_SENTENCE_TEXT) + System.lineSeparator();
37+
38+
static final String[][] EXPECTED_WORD_TEXT = {
39+
{"Pero", "la", "existencia", "de", "dos", "recién", "nacidos", "en", "la", "misma", "caja", "sólo", "podía", "deber", "se", "a", "un", "descuido", "de", "fábrica", "."},
40+
{"De", "allí", "las", "rebajas", "."},
41+
};
42+
43+
static final String[][] EXPECTED_LEMMA_TEXT = {
44+
{"pero", "el", "existencia", "de", "dos", "recién", "nacido", "en", "el", "mismo", "caja", "sólo", "poder", "deber", "él", "a", "uno", "descuido", "de", "fábrica", "."},
45+
{"de", "allí", "el", "rebaja", "."},
46+
};
47+
48+
static final String[][] EXPECTED_CPOS = {
49+
{"CCONJ", "DET", "NOUN", "ADP", "NUM", "ADV", "ADJ", "ADP", "DET", "DET", "NOUN", "ADV", "AUX", "VERB", "PRON", "ADP", "DET", "NOUN", "ADP", "NOUN", "PUNCT"},
50+
{"ADP", "ADV", "DET", "NOUN", "PUNCT"},
51+
};
52+
53+
static final String[][] EXPECTED_FEATS = {
54+
{
55+
null,
56+
"Definite=Def|Gender=Fem|Number=Sing|PronType=Art",
57+
"Gender=Fem|Number=Sing",
58+
null,
59+
"Number=Plur|NumForm=Word|NumType=Card",
60+
null,
61+
"Gender=Masc|Number=Plur|VerbForm=Part",
62+
null,
63+
"Definite=Def|Gender=Fem|Number=Sing|PronType=Art",
64+
"Gender=Fem|Number=Sing|PronType=Dem",
65+
"Gender=Fem|Number=Sing",
66+
null,
67+
"Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin",
68+
"VerbForm=Inf",
69+
"Case=Acc|Person=3|PrepCase=Npr|PronType=Prs|Reflex=Yes",
70+
null,
71+
"Definite=Ind|Gender=Masc|Number=Sing|PronType=Art",
72+
"Gender=Masc|Number=Sing",
73+
null,
74+
"Gender=Fem|Number=Sing",
75+
"PunctType=Peri",
76+
},
77+
{
78+
null,
79+
null,
80+
"Definite=Def|Gender=Fem|Number=Plur|PronType=Art",
81+
"Gender=Fem|Number=Plur",
82+
"PunctType=Peri",
83+
}
84+
};
85+
86+
static final String[][] EXPECTED_RELNS = {
87+
{ "advmod", "det", "nsubj", "case", "nummod", "advmod", "amod", "case", "det", "det", "nmod", "advmod", "aux", "root",
88+
"expl:pv", "case", "det", "obl:arg", "case", "nmod", "punct" },
89+
{ "case", "advmod", "det", "root", "punct" },
90+
};
91+
static final int[][] EXPECTED_HEADS = {
92+
{ 14, 3, 14, 7, 7, 7, 3, 11, 11, 9, 3, 14, 14, 0, 14, 18, 18, 14, 20, 18, 14 },
93+
{ 2, 4, 4, 0, 4 },
94+
};
3495

3596
@Test
3697
public void testReadingInCoNLLUFile() throws ClassNotFoundException, IOException {
37-
goldDocument = pipeline.process(exampleDocument);
3898
readInDocument = new CoNLLUReader(new Properties()).readCoNLLUFile(examplePath).get(0);
39-
// make some changes for sake of comparison
40-
// remove AfterAnnotation from read in
41-
// remove ParentAnnotation from gold
42-
for (CoreLabel token : goldDocument.get(CoreAnnotations.TokensAnnotation.class)) {
43-
token.remove(CoreAnnotations.ParentAnnotation.class);
99+
100+
assertTrue(readInDocument.containsKey(CoreAnnotations.TextAnnotation.class));
101+
assertTrue(readInDocument.containsKey(CoreAnnotations.TokensAnnotation.class));
102+
assertTrue(readInDocument.containsKey(CoreAnnotations.SentencesAnnotation.class));
103+
assertEquals(3, readInDocument.keySet().size());
104+
105+
// Compare text of the document and its sentences
106+
assertEquals(EXPECTED_TEXT, readInDocument.get(CoreAnnotations.TextAnnotation.class));
107+
List<CoreMap> sentences = readInDocument.get(CoreAnnotations.SentencesAnnotation.class);
108+
assertEquals(EXPECTED_SENTENCE_TEXT.length, sentences.size());
109+
for (int i = 0; i < EXPECTED_SENTENCE_TEXT.length; ++i) {
110+
assertEquals(EXPECTED_SENTENCE_TEXT[i], sentences.get(i).get(CoreAnnotations.TextAnnotation.class));
44111
}
45-
for (CoreLabel token : readInDocument.get(CoreAnnotations.TokensAnnotation.class)) {
46-
token.remove(CoreAnnotations.CoNLLUFeats.class);
112+
113+
// Compare sentence ids
114+
// Check number of keys on each sentence
115+
for (int i = 0; i < sentences.size(); ++i) {
116+
assertEquals(Integer.valueOf(i), sentences.get(i).get(CoreAnnotations.SentenceIndexAnnotation.class));
117+
assertEquals(4, sentences.get(i).keySet().size());
118+
}
119+
120+
// Check the document tokens and the sentence tokens lists are the same
121+
// The composite list on the document level should just be the sentence tokens gathered into one list
122+
List<CoreMap> allTokens = new ArrayList<>();
123+
for (int i = 0; i < sentences.size(); ++i) {
124+
allTokens.addAll(sentences.get(i).get(CoreAnnotations.TokensAnnotation.class));
47125
}
48-
// compare gold vs. read in
49-
// compare document text
50-
assertEquals(goldDocument.get(CoreAnnotations.TextAnnotation.class),
51-
readInDocument.get(CoreAnnotations.TextAnnotation.class));
52-
// compare tokens lists
53-
AnnotationComparator.compareTokensLists(goldDocument, readInDocument);
54-
assertEquals(goldDocument.get(CoreAnnotations.TokensAnnotation.class),
55-
readInDocument.get(CoreAnnotations.TokensAnnotation.class));
56-
// compare sentences
57-
for (int i = 0; i < goldDocument.get(CoreAnnotations.SentencesAnnotation.class).size(); i++) {
58-
CoreMap goldSentence = goldDocument.get(CoreAnnotations.SentencesAnnotation.class).get(i);
59-
CoreMap readInSentence = readInDocument.get(CoreAnnotations.SentencesAnnotation.class).get(i);
60-
// compare sentence text
61-
assertEquals(goldSentence.get(CoreAnnotations.TextAnnotation.class),
62-
readInSentence.get(CoreAnnotations.TextAnnotation.class));
63-
// compare token lists
64-
assertEquals(goldSentence.get(CoreAnnotations.TokensAnnotation.class),
65-
readInSentence.get(CoreAnnotations.TokensAnnotation.class));
66-
// compare semantic graphs
67-
SemanticGraph goldGraph =
68-
goldDocument.get(CoreAnnotations.SentencesAnnotation.class).get(i).get(
69-
SemanticGraphCoreAnnotations.BasicDependenciesAnnotation.class);
70-
SemanticGraph readInGraph =
71-
goldDocument.get(CoreAnnotations.SentencesAnnotation.class).get(i).get(
72-
SemanticGraphCoreAnnotations.BasicDependenciesAnnotation.class);
73-
assertEquals(goldGraph.toList(), readInGraph.toList());
126+
assertEquals(readInDocument.get(CoreAnnotations.TokensAnnotation.class), allTokens);
127+
128+
// Check the text on each of the words
129+
// Check the lemmas
130+
// Check indices and a couple other annotations we expect to be here
131+
for (int i = 0; i < sentences.size(); ++i) {
132+
CoreMap sentence = sentences.get(i);
133+
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
134+
assertEquals(EXPECTED_WORD_TEXT[i].length, tokens.size());
135+
assertEquals(EXPECTED_LEMMA_TEXT[i].length, tokens.size());
136+
assertEquals(EXPECTED_CPOS[i].length, tokens.size());
137+
for (int j = 0; j < tokens.size(); ++j) {
138+
CoreLabel token = tokens.get(j);
139+
assertEquals(EXPECTED_WORD_TEXT[i][j], token.value());
140+
assertEquals(EXPECTED_WORD_TEXT[i][j], token.word());
141+
assertEquals(EXPECTED_WORD_TEXT[i][j], token.get(CoreAnnotations.OriginalTextAnnotation.class));
142+
143+
assertEquals(EXPECTED_LEMMA_TEXT[i][j], token.lemma());
144+
assertEquals(EXPECTED_CPOS[i][j], token.tag());
145+
146+
assertEquals(Integer.valueOf(i), token.get(CoreAnnotations.SentenceIndexAnnotation.class));
147+
assertEquals(Integer.valueOf(j+1), token.get(CoreAnnotations.IndexAnnotation.class));
148+
149+
// all tokens should have a False isNewline
150+
assertFalse(token.get(CoreAnnotations.IsNewlineAnnotation.class));
151+
}
152+
}
153+
154+
// Check the MWT features
155+
for (int i = 0; i < sentences.size(); ++i) {
156+
CoreMap sentence = sentences.get(i);
157+
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
158+
for (int j = 0; j < tokens.size(); ++j) {
159+
CoreLabel token = tokens.get(j);
160+
// words 14-15 (indexed one lower here) are the only MWT in this document
161+
// otherwise, all fields should be false
162+
if (i == 0 && j == 13) {
163+
assertTrue(token.get(CoreAnnotations.IsMultiWordTokenAnnotation.class));
164+
assertTrue(token.get(CoreAnnotations.IsFirstWordOfMWTAnnotation.class));
165+
assertEquals("deberse", token.get(CoreAnnotations.MWTTokenTextAnnotation.class));
166+
} else if (i == 0 && j == 14) {
167+
assertTrue(token.get(CoreAnnotations.IsMultiWordTokenAnnotation.class));
168+
assertFalse(token.get(CoreAnnotations.IsFirstWordOfMWTAnnotation.class));
169+
assertEquals("deberse", token.get(CoreAnnotations.MWTTokenTextAnnotation.class));
170+
} else {
171+
assertFalse(token.get(CoreAnnotations.IsMultiWordTokenAnnotation.class));
172+
assertFalse(token.get(CoreAnnotations.IsFirstWordOfMWTAnnotation.class));
173+
assertFalse(token.containsKey(CoreAnnotations.MWTTokenTextAnnotation.class));
174+
}
175+
}
176+
}
177+
178+
// Check the Before & After features
179+
// TODO: May need to reconsider the end of sentence treatment
180+
for (int i = 0; i < sentences.size(); ++i) {
181+
CoreMap sentence = sentences.get(i);
182+
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
183+
for (int j = 0; j < tokens.size(); ++j) {
184+
CoreLabel token = tokens.get(j);
185+
if (j == tokens.size() - 1) {
186+
assertEquals("\n", token.after());
187+
} else if (j == tokens.size() - 2) {
188+
assertEquals("", token.after());
189+
} else {
190+
// TODO: after() should be "" for an MWT
191+
// it just doesn't get marked on the CoNLLU
192+
assertEquals(" ", token.after());
193+
}
194+
195+
if (i == 0 && j == 0) {
196+
assertEquals("", token.before());
197+
} else if (j == 0) {
198+
assertEquals("\n", token.before());
199+
} else if (j == tokens.size() - 1) {
200+
assertEquals("", token.before());
201+
} else {
202+
assertEquals(" ", token.before());
203+
}
204+
}
205+
}
206+
207+
// Check that these fields are set
208+
// Perhaps not checking the values of the offsets, though
209+
int tokenCount = 0;
210+
for (int i = 0; i < sentences.size(); ++i) {
211+
CoreMap sentence = sentences.get(i);
212+
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
213+
for (int j = 0; j < tokens.size(); ++j) {
214+
CoreLabel token = tokens.get(j);
215+
assertTrue(token.containsKey(CoreAnnotations.CharacterOffsetBeginAnnotation.class));
216+
assertTrue(token.containsKey(CoreAnnotations.CharacterOffsetEndAnnotation.class));
217+
assertEquals(Integer.valueOf(tokenCount), token.get(CoreAnnotations.TokenBeginAnnotation.class));
218+
assertEquals(Integer.valueOf(tokenCount+1), token.get(CoreAnnotations.TokenEndAnnotation.class));
219+
++tokenCount;
220+
}
221+
}
222+
223+
// check the features and that there are no fields currently unaccounted for
224+
for (int i = 0; i < sentences.size(); ++i) {
225+
CoreMap sentence = sentences.get(i);
226+
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
227+
assertEquals(EXPECTED_FEATS[i].length, tokens.size());
228+
for (int j = 0; j < tokens.size(); ++j) {
229+
CoreLabel token = tokens.get(j);
230+
231+
String expected = EXPECTED_FEATS[i][j];
232+
int expectedKeys = 16;
233+
234+
if (expected == null) {
235+
assertFalse(token.containsKey(CoreAnnotations.CoNLLUFeats.class));
236+
} else {
237+
expectedKeys += 1;
238+
String feats = token.get(CoreAnnotations.CoNLLUFeats.class).toString();
239+
assertEquals(expected, feats);
240+
}
241+
242+
// the MWT token specifically gets one more field, the MWT text
243+
if (i == 0 && (j == 13 || j == 14)) {
244+
expectedKeys += 1;
245+
}
246+
assertEquals(expectedKeys, token.keySet().size());
247+
248+
// The known fields should be the ones checked above:
249+
// CoreAnnotations.TextAnnotation
250+
// CoreAnnotations.ValueAnnotation
251+
// CoreAnnotations.OriginalTextAnnotation
252+
// CoreAnnotations.IsNewlineAnnotation
253+
// CoreAnnotations.LemmaAnnotation
254+
// CoreAnnotations.PartOfSpeechAnnotation
255+
// CoreAnnotations.IndexAnnotation
256+
// CoreAnnotations.AfterAnnotation
257+
// CoreAnnotations.BeforeAnnotation
258+
// CoreAnnotations.IsMultiWordTokenAnnotation
259+
// CoreAnnotations.IsFirstWordOfMWTAnnotation
260+
// CoreAnnotations.CharacterOffsetBeginAnnotation
261+
// CoreAnnotations.CharacterOffsetEndAnnotation
262+
// CoreAnnotations.TokenBeginAnnotation
263+
// CoreAnnotations.TokenEndAnnotation
264+
// CoreAnnotations.SentenceIndexAnnotation
265+
// and sometimes
266+
// CoreAnnotations.CoNLLUFeats
267+
// CoreAnnotations.MWTTokenTextAnnotation
268+
//
269+
// TODO: make it always add a Feats, even if it's not present?
270+
}
271+
}
272+
273+
// compare the SemanticGraph
274+
for (int i = 0; i < sentences.size(); ++i) {
275+
CoreMap sentence = sentences.get(i);
276+
SemanticGraph graph = sentence.get(SemanticGraphCoreAnnotations.BasicDependenciesAnnotation.class);
277+
assertNotNull(graph);
278+
279+
List<IndexedWord> vertices = graph.vertexListSorted();
280+
assertEquals(EXPECTED_WORD_TEXT[i].length, vertices.size());
281+
assertEquals(EXPECTED_RELNS[i].length, vertices.size());
282+
assertEquals(EXPECTED_HEADS[i].length, vertices.size());
283+
for (int j = 0; j < vertices.size(); ++j) {
284+
IndexedWord vertex = vertices.get(j);
285+
assertEquals(EXPECTED_WORD_TEXT[i][j], vertex.value());
286+
287+
// each word should be properly indexed with the sentIndex and position in the sentence
288+
assertEquals(i, vertex.sentIndex());
289+
// j+1 because the arrows are laid out with 0 as root, words with a 1-based index
290+
assertEquals(j+1, vertex.index());
291+
292+
if (EXPECTED_HEADS[i][j] == 0) {
293+
assertTrue(graph.isRoot(vertex));
294+
continue;
295+
}
296+
297+
// If not a root, then the word should have exactly one parent
298+
// The HEAD and RELNS arrays specify the expected parent and relation of the edge
299+
List<SemanticGraphEdge> edges = graph.getIncomingEdgesSorted(vertex);
300+
assertEquals(1, edges.size());
301+
assertEquals(EXPECTED_HEADS[i][j], edges.get(0).getGovernor().index());
302+
assertEquals(EXPECTED_RELNS[i][j], edges.get(0).getRelation().toString());
303+
}
74304
}
75305
}
76306
}

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