Module: SpaCy
- Defined in:
- lib/rbbt/nlp/spaCy.rb
Constant Summary collapse
- TOKEN_PROPERTIES =
%w(lemma_ is_punct is_space shape_ pos_ tag_)
- CHUNK_PROPERTIES =
%w(lemma_)
Class Method Summary collapse
- .chunk_dep_graph(text, reverse = false, lang = 'en_core_web_md') ⇒ Object
- .chunk_segments(text, lang = 'en_core_web_sm') ⇒ Object
- .chunks(text, lang = 'en_core_web_sm') ⇒ Object
- .config(base, target = nil) ⇒ Object
- .dep_graph(text, reverse = false, lang = 'en_core_web_md') ⇒ Object
- .nlp(lang = 'en_core_web_md') ⇒ Object
- .paths(text, source, target, reverse = true, lang = 'en_core_web_md') ⇒ Object
- .segments(text, lang = 'en_core_web_sm') ⇒ Object
- .tokens(text, lang = 'en_core_web_sm') ⇒ Object
Class Method Details
.chunk_dep_graph(text, reverse = false, lang = 'en_core_web_md') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 116 def self.chunk_dep_graph(text, reverse = false, lang = 'en_core_web_md') associations = dep_graph(text, false, lang) chunks = self.chunk_segments(text, lang) tokens = self.segments(text, lang) index = Segment.index(tokens + chunks) chunks.each do |chunk| target_token_ids = chunk.dep.split(";").collect do|dep| type, target_pos = dep.split("->") index[target_pos.to_i] end.flatten target_tokens = target_token_ids.collect do |target_token_id| range = Range.new(*target_token_id.split(":").last.split("..").map(&:to_i)) range.collect do |pos| index[pos] end.uniq end.flatten associations[chunk.segid] = target_tokens end if reverse old = associations.dup old.each do |s,ts| ts.each do |t| associations[t] ||= [] associations[t] += [s] unless associations[t].include?(s) end end end associations end |
.chunk_segments(text, lang = 'en_core_web_sm') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 67 def self.chunk_segments(text, lang = 'en_core_web_sm') docid = text.docid if Document === text corpus = text.corpus if Document === text chunks = self.chunks(text, lang).collect do |chunk| info = {} CHUNK_PROPERTIES.each do |p| info[p] = chunk.instance_eval(p.to_s) end start = eend = nil deps = [] RbbtPython.iterate chunk.__iter__ do |token| start = token.idx if start.nil? eend = start + chunk.text.length if eend.nil? deps << token.idx.to_s + ":" + token.dep_ + "->" + token.head.idx.to_s if token.head.idx < start || token.head.idx > eend end info[:type] = "SpaCy" info[:offset] = chunk.__iter__.__next__.idx info[:dep] = deps * ";" info[:docid] = docid if docid info[:corpus] = corpus if corpus SpaCySpan.setup(chunk.text, info) end chunks end |
.chunks(text, lang = 'en_core_web_sm') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 33 def self.chunks(text, lang = 'en_core_web_sm') tokens = [] nlp = nlp(lang) doc = nlp.call(text) chunks = doc.noun_chunks.__iter__ RbbtPython.iterate chunks do |item| tokens << item end tokens end |
.config(base, target = nil) ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 166 def self.config(base, target = nil) TmpFile.with_file(base) do |baseconfig| if target CMD.cmd(:spacy, "init fill-config #{baseconfig} #{target}") else TmpFile.with_file do |tmptarget| CMD.cmd(:spacy, "init fill-config #{baseconfig} #{tmptarget}") Open.read(targetconfig) end end end end |
.dep_graph(text, reverse = false, lang = 'en_core_web_md') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 93 def self.dep_graph(text, reverse = false, lang = 'en_core_web_md') tokens = self.segments(text, lang) index = Segment.index(tokens) associations = {} tokens.each do |token| type, target_pos = token.dep.split("->") target_tokens = index[target_pos.to_i] associations[token.segid] = target_tokens end if reverse old = associations.dup old.each do |s,ts| ts.each do |t| associations[t] ||= [] associations[t] += [s] unless associations[t].include?(s) end end end associations end |
.nlp(lang = 'en_core_web_md') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 12 def self.nlp(lang = 'en_core_web_md') @@nlp ||= {} @@nlp[lang] ||= RbbtPython.run :spacy do spacy.load(lang) end end |
.paths(text, source, target, reverse = true, lang = 'en_core_web_md') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 151 def self.paths(text, source, target, reverse = true, lang = 'en_core_web_md') graph = SpaCy.chunk_dep_graph(text, reverse, lang) chunk_index = Segment.index(SpaCy.chunk_segments(text, lang)) source_id = chunk_index[source.offset.to_i].first || source.segid target_id = chunk_index[target.offset.to_i].first || target.segid path = Paths.dijkstra(graph, source_id, [target_id]) return nil if path.nil? path.reverse end |
.segments(text, lang = 'en_core_web_sm') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 48 def self.segments(text, lang = 'en_core_web_sm') docid = text.docid if Document === text corpus = text.corpus if Document === text tokens = self.tokens(text, lang).collect do |token| info = {} TOKEN_PROPERTIES.each do |p| info[p] = token.instance_eval(p.to_s) end info[:type] = "SpaCy" info[:offset] = token.idx info[:dep] = token.dep_ + "->" + token.head.idx.to_s info[:docid] = docid if docid info[:corpus] = corpus if corpus SpaCyToken.setup(token.text, info) end tokens end |
.tokens(text, lang = 'en_core_web_sm') ⇒ Object
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# File 'lib/rbbt/nlp/spaCy.rb', line 19 def self.tokens(text, lang = 'en_core_web_sm') tokens = [] nlp = nlp(lang) doc = nlp.call(text) doc.__len__.times do |i| tokens << doc.__getitem__(i) end tokens end |