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Fix bug where DefaultValueSlot default values are not applied when sl…
…otmatch fails (#21) - currently, when the NER model extracts some tokens it never applies DefaultValueSlot - i.e. DefaultValueSlot was only used when the model failed to extract any tokens - bug wasnt that significant because most default values were empty string anyway
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...rs-opennlp-ner/src/main/java/com/rabidgremlin/mutters/opennlp/ner/OpenNLPSlotMatcher.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,132 +1,133 @@ | ||
| package com.rabidgremlin.mutters.opennlp.ner; | ||
|
|
||
| import java.net.URL; | ||
| import java.util.HashMap; | ||
|
|
||
| import org.slf4j.Logger; | ||
| import org.slf4j.LoggerFactory; | ||
|
|
||
| import com.rabidgremlin.mutters.core.Context; | ||
| import com.rabidgremlin.mutters.core.Intent; | ||
| import com.rabidgremlin.mutters.core.Slot; | ||
| import com.rabidgremlin.mutters.core.SlotMatch; | ||
| import com.rabidgremlin.mutters.core.SlotMatcher; | ||
| import com.rabidgremlin.mutters.core.Tokenizer; | ||
| import com.rabidgremlin.mutters.slots.DefaultValueSlot; | ||
|
|
||
| import opennlp.tools.namefind.NameFinderME; | ||
| import opennlp.tools.namefind.TokenNameFinderModel; | ||
| import opennlp.tools.util.Span; | ||
|
|
||
| /** | ||
| * Implements a SlotMatcher that uses OpenNLP's NER framework. | ||
| * | ||
| * @author rabidgremlin | ||
| * | ||
| */ | ||
| public class OpenNLPSlotMatcher | ||
| implements SlotMatcher | ||
| { | ||
| /** Logger. */ | ||
| private Logger log = LoggerFactory.getLogger(OpenNLPSlotMatcher.class); | ||
|
|
||
| /** Map of NER models. */ | ||
| private HashMap<String, TokenNameFinderModel> nerModels = new HashMap<String, TokenNameFinderModel>(); | ||
|
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| /** Map of slot models. These share the NER models. */ | ||
| private HashMap<String, TokenNameFinderModel> slotModels = new HashMap<String, TokenNameFinderModel>(); | ||
|
|
||
| /** The tokenizer to use. */ | ||
| private Tokenizer tokenizer; | ||
|
|
||
| /** | ||
| * Constructor. Allows tokenizer to be supplied because NER can use case etc as cues, so may require different | ||
| * tokenizer than used for intent matching. | ||
| * | ||
| * @param tokenizer The tokenizer to use on an utterance for NER. | ||
| */ | ||
| public OpenNLPSlotMatcher(Tokenizer tokenizer) | ||
| { | ||
| this.tokenizer = tokenizer; | ||
| } | ||
|
|
||
| /** | ||
| * This set the NER model to use for a slot. | ||
| * | ||
| * @param slotName The name of the slot. Should match the name of slots on intents added to the matcher. | ||
| * @param nerModel The file name of the NER model. This file must be on the classpath. | ||
| */ | ||
| public void addSlotModel(String slotName, String nerModel) | ||
| { | ||
| TokenNameFinderModel tnfModel = nerModels.get(nerModel); | ||
| if (tnfModel == null) | ||
| { | ||
| try | ||
| { | ||
| URL modelUrl = Thread.currentThread().getContextClassLoader().getResource(nerModel); | ||
| tnfModel = new TokenNameFinderModel(modelUrl); | ||
| } | ||
| catch (Exception e) | ||
| { | ||
| throw new IllegalArgumentException("Unable to load NER model", e); | ||
| } | ||
| } | ||
|
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| slotModels.put(slotName.toLowerCase(), tnfModel); | ||
| } | ||
|
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| @Override | ||
| public HashMap<Slot, SlotMatch> match(Context context, Intent intent, String utterance) | ||
| { | ||
| String[] utteranceTokens = tokenizer.tokenize(utterance); | ||
|
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| HashMap<Slot, SlotMatch> matchedSlots = new HashMap<Slot, SlotMatch>(); | ||
|
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| for (Slot slot : intent.getSlots()) | ||
| { | ||
| log.debug("Looking for Slot {}", slot.getName()); | ||
|
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| TokenNameFinderModel tnfModel = slotModels.get(slot.getName().toLowerCase()); | ||
| if (tnfModel == null) | ||
| { | ||
| log.warn("Could not find NER model for slot {}", slot.getName()); | ||
| continue; | ||
| } | ||
|
|
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| NameFinderME nameFinder = new NameFinderME(tnfModel); | ||
| Span[] spans = nameFinder.find(utteranceTokens); | ||
|
|
||
| if (spans.length > 0) | ||
| { | ||
| String[] matches = Span.spansToStrings(spans, utteranceTokens); | ||
|
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| log.debug("Matching for {} against {}", slot.getName(), matches); | ||
|
|
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| // TODO what to do with multi matches? | ||
| SlotMatch match = slot.match(matches[0], context); | ||
| if (match != null) | ||
| { | ||
| matchedSlots.put(slot, match); | ||
| log.debug("Match found {}", match); | ||
| } | ||
| else | ||
| { | ||
| log.debug("No Match found slot: {} text: {} ", slot.getName(), matches); | ||
| } | ||
| } | ||
| else if (slot instanceof DefaultValueSlot) | ||
| { | ||
| Object defaultValue = ((DefaultValueSlot) slot).getDefaultValue(); | ||
| matchedSlots.put(slot, new SlotMatch(slot, utterance, defaultValue)); | ||
| log.debug("No Match found slot: {} Using default value: {} ", slot.getName(), defaultValue); | ||
| } | ||
| else | ||
| { | ||
| log.debug("Did not find slot {} utteranceTokens {} ", slot.getName(), utteranceTokens); | ||
| } | ||
| } | ||
|
|
||
| return matchedSlots; | ||
| } | ||
|
|
||
| } | ||
| package com.rabidgremlin.mutters.opennlp.ner; | ||
|
|
||
| import java.net.URL; | ||
| import java.util.HashMap; | ||
|
|
||
| import org.slf4j.Logger; | ||
| import org.slf4j.LoggerFactory; | ||
|
|
||
| import com.rabidgremlin.mutters.core.Context; | ||
| import com.rabidgremlin.mutters.core.Intent; | ||
| import com.rabidgremlin.mutters.core.Slot; | ||
| import com.rabidgremlin.mutters.core.SlotMatch; | ||
| import com.rabidgremlin.mutters.core.SlotMatcher; | ||
| import com.rabidgremlin.mutters.core.Tokenizer; | ||
| import com.rabidgremlin.mutters.slots.DefaultValueSlot; | ||
|
|
||
| import opennlp.tools.namefind.NameFinderME; | ||
| import opennlp.tools.namefind.TokenNameFinderModel; | ||
| import opennlp.tools.util.Span; | ||
|
|
||
| /** | ||
| * Implements a SlotMatcher that uses OpenNLP's NER framework. | ||
| * | ||
| * @author rabidgremlin | ||
| * | ||
| */ | ||
| public class OpenNLPSlotMatcher | ||
| implements SlotMatcher | ||
| { | ||
| /** Logger. */ | ||
| private Logger log = LoggerFactory.getLogger(OpenNLPSlotMatcher.class); | ||
|
|
||
| /** Map of NER models. */ | ||
| private HashMap<String, TokenNameFinderModel> nerModels = new HashMap<String, TokenNameFinderModel>(); | ||
|
|
||
| /** Map of slot models. These share the NER models. */ | ||
| private HashMap<String, TokenNameFinderModel> slotModels = new HashMap<String, TokenNameFinderModel>(); | ||
|
|
||
| /** The tokenizer to use. */ | ||
| private Tokenizer tokenizer; | ||
|
|
||
| /** | ||
| * Constructor. Allows tokenizer to be supplied because NER can use case etc as cues, so may require different | ||
| * tokenizer than used for intent matching. | ||
| * | ||
| * @param tokenizer The tokenizer to use on an utterance for NER. | ||
| */ | ||
| public OpenNLPSlotMatcher(Tokenizer tokenizer) | ||
| { | ||
| this.tokenizer = tokenizer; | ||
| } | ||
|
|
||
| /** | ||
| * This set the NER model to use for a slot. | ||
| * | ||
| * @param slotName The name of the slot. Should match the name of slots on intents added to the matcher. | ||
| * @param nerModel The file name of the NER model. This file must be on the classpath. | ||
| */ | ||
| public void addSlotModel(String slotName, String nerModel) | ||
| { | ||
| TokenNameFinderModel tnfModel = nerModels.get(nerModel); | ||
| if (tnfModel == null) | ||
| { | ||
| try | ||
| { | ||
| URL modelUrl = Thread.currentThread().getContextClassLoader().getResource(nerModel); | ||
| tnfModel = new TokenNameFinderModel(modelUrl); | ||
| } | ||
| catch (Exception e) | ||
| { | ||
| throw new IllegalArgumentException("Unable to load NER model", e); | ||
| } | ||
| } | ||
|
|
||
| slotModels.put(slotName.toLowerCase(), tnfModel); | ||
| } | ||
|
|
||
| @Override | ||
| public HashMap<Slot, SlotMatch> match(Context context, Intent intent, String utterance) | ||
| { | ||
| String[] utteranceTokens = tokenizer.tokenize(utterance); | ||
|
|
||
| HashMap<Slot, SlotMatch> matchedSlots = new HashMap<Slot, SlotMatch>(); | ||
|
|
||
| for (Slot slot : intent.getSlots()) | ||
| { | ||
| log.debug("Looking for Slot {}", slot.getName()); | ||
|
|
||
| TokenNameFinderModel tnfModel = slotModels.get(slot.getName().toLowerCase()); | ||
| if (tnfModel == null) | ||
| { | ||
| log.warn("Could not find NER model for slot {}", slot.getName()); | ||
| continue; | ||
| } | ||
|
|
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| NameFinderME nameFinder = new NameFinderME(tnfModel); | ||
| Span[] spans = nameFinder.find(utteranceTokens); | ||
|
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| boolean slotMatched = false; | ||
| if (spans.length > 0) | ||
| { | ||
| String[] matches = Span.spansToStrings(spans, utteranceTokens); | ||
|
|
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| log.debug("Matching for {} against {}", slot.getName(), matches); | ||
|
|
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| // TODO what to do with multi matches? | ||
| SlotMatch match = slot.match(matches[0], context); | ||
| if (match != null) | ||
| { | ||
| matchedSlots.put(slot, match); | ||
| slotMatched = true; | ||
| log.debug("Match found {}", match); | ||
| } | ||
| else | ||
| { | ||
| log.debug("No Match found slot: {} text: {} ", slot.getName(), matches); | ||
| } | ||
| } | ||
|
|
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| if (!slotMatched && slot instanceof DefaultValueSlot) | ||
| { | ||
| Object defaultValue = ((DefaultValueSlot) slot).getDefaultValue(); | ||
| matchedSlots.put(slot, new SlotMatch(slot, utterance, defaultValue)); | ||
| log.debug("No Match found slot: {} Using default value: {} ", slot.getName(), defaultValue); | ||
| } | ||
| else | ||
| { | ||
| log.debug("Did not find slot {} utteranceTokens {} ", slot.getName(), utteranceTokens); | ||
| } | ||
| } | ||
| return matchedSlots; | ||
| } | ||
| } |