paddle.v2.evaluator.chunk(*args, **kwargs)Chunk evaluator is used to evaluate segment labelling accuracy for a -sequence. It calculates the chunk detection F1 score.
-A chunk is correctly detected if its beginning, end and type are correct. -Other chunk type is ignored.
-For each label in the label sequence, we have:
-tagType = label % numTagType
-chunkType = label / numTagType
-otherChunkType = numChunkTypes
+sequence. It calculates precision, recall and F1 scores for the chunk detection.
+To use chunk evaluator, several concepts need to be clarified firstly.
+We can name a label by combining tag type and chunk type. (ie. B-ORG for begining of an organization name)
+The construction of label dictionary should obey the following rules:
+Scheme Description
+plain Use the same label for the whole chunk.
+IOB Two labels for chunk type X, B-X for chunk begining and I-X for chunk inside.
+IOE Two labels for chunk type X, E-X for chunk ending and I-X for chunk inside.
+IOBES Four labels for chunk type X, B-X for chunk begining, I-X for chunk inside, E-X for chunk end and S-X for single word chunk.
+To make it clear, let’s illustrate by an NER example. +Assuming that there are three named entity types including ORG, PER and LOC which are called ‘chunk type’ here, +if ‘IOB’ scheme were used, the label set will be extended to a set including B-ORG, I-ORG, B-PER, I-PER, B-LOC, I-LOC and O, +in which B-ORG for begining of ORG and I-ORG for inside of ORG. +Prefixes which are called ‘tag type’ here are added to chunk types and there are two tag types including B and I. +Of course, the training data should be labeled accordingly.
+The following table are equations to extract tag type and chunk type from a label.
+tagType = label % numTagType
+chunkType = label / numTagType
+otherChunkType = numChunkTypes
+The following table shows the mapping rule between tagType and tag type in each scheme.
+Scheme Begin Inside End Single
+plain 0 - - -
+IOB 0 1 - -
+IOE - 0 1 -
+IOBES 0 1 2 3
The total number of different labels is numTagType*numChunkTypes+1. -We support 4 labelling scheme. -The tag type for each of the scheme is shown as follows:
-Scheme Begin Inside End Single
-plain 0 - - -
-IOB 0 1 - -
-IOE - 0 1 -
-IOBES 0 1 2 3
+Continue the NER example, and the label dict should look like this to satify above equations:
+B-ORG 0
+I-ORG 1
+B-PER 2
+I-PER 3
+B-LOC 4
+I-LOC 5
+O 6
-‘plain’ means the whole chunk must contain exactly the same chunk label.
+In this example, chunkType has three values: 0 for ORG, 1 for PER, 2 for LOC, because the scheme is
+“IOB” so tagType has two values: 0 for B and 1 for I.
+Here we will use I-LOC to explain the above mapping rules in detail.
+For I-LOC, the label id is 5, so we can get tagType=1 and chunkType=2, which means I-LOC is a part of NER chunk LOC
+and the tag is I.
The simple usage is:
eval = chunk_evaluator(input, label, chunk_scheme, num_chunk_types)
diff --git a/develop/doc/searchindex.js b/develop/doc/searchindex.js
index dbfcd27214b7a1729c0b3ab0e3095e275ab5cdde..df184451cf22f74ee68ae2fc4f183b9253ad67eb 100644
--- a/develop/doc/searchindex.js
+++ b/develop/doc/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/develop/doc_cn/api/v2/config/evaluators.html b/develop/doc_cn/api/v2/config/evaluators.html
index 658b136af3f58f75929ea925cfbe5bb3249e97b9..40f428f16d073b538b584a71562184348654ba9b 100644
--- a/develop/doc_cn/api/v2/config/evaluators.html
+++ b/develop/doc_cn/api/v2/config/evaluators.html
@@ -294,26 +294,62 @@ label for ctc
class paddle.v2.evaluator.chunk(*args, **kwargs)
Chunk evaluator is used to evaluate segment labelling accuracy for a
-sequence. It calculates the chunk detection F1 score.
-A chunk is correctly detected if its beginning, end and type are correct.
-Other chunk type is ignored.
-For each label in the label sequence, we have:
-tagType = label % numTagType
-chunkType = label / numTagType
-otherChunkType = numChunkTypes
+sequence. It calculates precision, recall and F1 scores for the chunk detection.
+To use chunk evaluator, several concepts need to be clarified firstly.
+
+- Chunk type is the type of the whole chunk and a chunk consists of one or several words. (For example in NER, ORG for organization name, PER for person name etc.)
+- Tag type indicates the position of a word in a chunk. (B for begin, I for inside, E for end, S for single)
+
+We can name a label by combining tag type and chunk type. (ie. B-ORG for begining of an organization name)
+The construction of label dictionary should obey the following rules:
+
+- Use one of the listed labelling schemes. These schemes differ in ways indicating chunk boundry.
+
+Scheme Description
+plain Use the same label for the whole chunk.
+IOB Two labels for chunk type X, B-X for chunk begining and I-X for chunk inside.
+IOE Two labels for chunk type X, E-X for chunk ending and I-X for chunk inside.
+IOBES Four labels for chunk type X, B-X for chunk begining, I-X for chunk inside, E-X for chunk end and S-X for single word chunk.
+
+
+To make it clear, let’s illustrate by an NER example.
+Assuming that there are three named entity types including ORG, PER and LOC which are called ‘chunk type’ here,
+if ‘IOB’ scheme were used, the label set will be extended to a set including B-ORG, I-ORG, B-PER, I-PER, B-LOC, I-LOC and O,
+in which B-ORG for begining of ORG and I-ORG for inside of ORG.
+Prefixes which are called ‘tag type’ here are added to chunk types and there are two tag types including B and I.
+Of course, the training data should be labeled accordingly.
+
+- Mapping is done correctly by the listed equations and assigning protocol.
+
+The following table are equations to extract tag type and chunk type from a label.
+tagType = label % numTagType
+chunkType = label / numTagType
+otherChunkType = numChunkTypes
+
+
+The following table shows the mapping rule between tagType and tag type in each scheme.
+Scheme Begin Inside End Single
+plain 0 - - -
+IOB 0 1 - -
+IOE - 0 1 -
+IOBES 0 1 2 3
-The total number of different labels is numTagType*numChunkTypes+1.
-We support 4 labelling scheme.
-The tag type for each of the scheme is shown as follows:
-Scheme Begin Inside End Single
-plain 0 - - -
-IOB 0 1 - -
-IOE - 0 1 -
-IOBES 0 1 2 3
+Continue the NER example, and the label dict should look like this to satify above equations:
+B-ORG 0
+I-ORG 1
+B-PER 2
+I-PER 3
+B-LOC 4
+I-LOC 5
+O 6
-‘plain’ means the whole chunk must contain exactly the same chunk label.
+In this example, chunkType has three values: 0 for ORG, 1 for PER, 2 for LOC, because the scheme is
+“IOB” so tagType has two values: 0 for B and 1 for I.
+Here we will use I-LOC to explain the above mapping rules in detail.
+For I-LOC, the label id is 5, so we can get tagType=1 and chunkType=2, which means I-LOC is a part of NER chunk LOC
+and the tag is I.
The simple usage is:
eval = chunk_evaluator(input, label, chunk_scheme, num_chunk_types)
diff --git a/develop/doc_cn/searchindex.js b/develop/doc_cn/searchindex.js
index 9b2741e9ebe181d27741c4fa513702d1c50a562e..8cbef0816f4b486977ac1251c751aeeb781017eb 100644
--- a/develop/doc_cn/searchindex.js
+++ b/develop/doc_cn/searchindex.js
@@ -1 +1 @@
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