import numpy import io import json import ujson import random import re import os from os import path from libc.string cimport memset try: import ujson as json except ImportError: import json from .syntax import nonproj def tags_to_entities(tags): entities = [] start = None for i, tag in enumerate(tags): if tag.startswith('O'): # TODO: We shouldn't be getting these malformed inputs. Fix this. if start is not None: start = None continue elif tag == '-': continue elif tag.startswith('I'): assert start is not None, tags[:i] continue if tag.startswith('U'): entities.append((tag[2:], i, i)) elif tag.startswith('B'): start = i elif tag.startswith('L'): entities.append((tag[2:], start, i)) start = None else: raise Exception(tag) return entities def align(cand_words, gold_words): cost, edit_path = _min_edit_path(cand_words, gold_words) alignment = [] i_of_gold = 0 for move in edit_path: if move == 'M': alignment.append(i_of_gold) i_of_gold += 1 elif move == 'S': alignment.append(None) i_of_gold += 1 elif move == 'D': alignment.append(None) elif move == 'I': i_of_gold += 1 else: raise Exception(move) return alignment punct_re = re.compile(r'\W') def _min_edit_path(cand_words, gold_words): cdef: Pool mem int i, j, n_cand, n_gold int* curr_costs int* prev_costs # TODO: Fix this --- just do it properly, make the full edit matrix and # then walk back over it... # Preprocess inputs cand_words = [punct_re.sub('', w) for w in cand_words] gold_words = [punct_re.sub('', w) for w in gold_words] if cand_words == gold_words: return 0, ''.join(['M' for _ in gold_words]) mem = Pool() n_cand = len(cand_words) n_gold = len(gold_words) # Levenshtein distance, except we need the history, and we may want different # costs. # Mark operations with a string, and score the history using _edit_cost. previous_row = [] prev_costs = mem.alloc(n_gold + 1, sizeof(int)) curr_costs = mem.alloc(n_gold + 1, sizeof(int)) for i in range(n_gold + 1): cell = '' for j in range(i): cell += 'I' previous_row.append('I' * i) prev_costs[i] = i for i, cand in enumerate(cand_words): current_row = ['D' * (i + 1)] curr_costs[0] = i+1 for j, gold in enumerate(gold_words): if gold.lower() == cand.lower(): s_cost = prev_costs[j] i_cost = curr_costs[j] + 1 d_cost = prev_costs[j + 1] + 1 else: s_cost = prev_costs[j] + 1 i_cost = curr_costs[j] + 1 d_cost = prev_costs[j + 1] + (1 if cand else 0) if s_cost <= i_cost and s_cost <= d_cost: best_cost = s_cost best_hist = previous_row[j] + ('M' if gold == cand else 'S') elif i_cost <= s_cost and i_cost <= d_cost: best_cost = i_cost best_hist = current_row[j] + 'I' else: best_cost = d_cost best_hist = previous_row[j + 1] + 'D' current_row.append(best_hist) curr_costs[j+1] = best_cost previous_row = current_row for j in range(len(gold_words) + 1): prev_costs[j] = curr_costs[j] curr_costs[j] = 0 return prev_costs[n_gold], previous_row[-1] def read_json_file(loc, docs_filter=None): print loc if path.isdir(loc): for filename in os.listdir(loc): yield from read_json_file(path.join(loc, filename)) else: with open(loc) as file_: docs = json.load(file_) for doc in docs: if docs_filter is not None and not docs_filter(doc): continue paragraphs = [] for paragraph in doc['paragraphs']: sents = [] for sent in paragraph['sentences']: words = [] ids = [] tags = [] heads = [] labels = [] ner = [] for i, token in enumerate(sent['tokens']): words.append(token['orth']) ids.append(i) tags.append(token['tag']) heads.append(token['head'] + i) labels.append(token['dep']) # Ensure ROOT label is case-insensitive if labels[-1].lower() == 'root': labels[-1] = 'ROOT' ner.append(token.get('ner', '-')) sents.append(( (ids, words, tags, heads, labels, ner), sent.get('brackets', []))) if sents: yield (paragraph.get('raw', None), sents) def _iob_to_biluo(tags): out = [] curr_label = None tags = list(tags) while tags: out.extend(_consume_os(tags)) out.extend(_consume_ent(tags)) return out def _consume_os(tags): while tags and tags[0] == 'O': yield tags.pop(0) def _consume_ent(tags): if not tags: return [] target = tags.pop(0).replace('B', 'I') length = 1 while tags and tags[0] == target: length += 1 tags.pop(0) label = target[2:] if length == 1: return ['U-' + label] else: start = 'B-' + label end = 'L-' + label middle = ['I-%s' % label for _ in range(1, length - 1)] return [start] + middle + [end] cdef class GoldParse: def __init__(self, tokens, annot_tuples, brackets=tuple(), make_projective=False): self.mem = Pool() self.loss = 0 self.length = len(tokens) # These are filled by the tagger/parser/entity recogniser self.c.tags = self.mem.alloc(len(tokens), sizeof(int)) self.c.heads = self.mem.alloc(len(tokens), sizeof(int)) self.c.labels = self.mem.alloc(len(tokens), sizeof(int)) self.c.ner = self.mem.alloc(len(tokens), sizeof(Transition)) self.c.brackets = self.mem.alloc(len(tokens), sizeof(int*)) for i in range(len(tokens)): self.c.brackets[i] = self.mem.alloc(len(tokens), sizeof(int)) self.tags = [None] * len(tokens) self.heads = [None] * len(tokens) self.labels = [''] * len(tokens) self.ner = ['-'] * len(tokens) self.cand_to_gold = align([t.orth_ for t in tokens], annot_tuples[1]) self.gold_to_cand = align(annot_tuples[1], [t.orth_ for t in tokens]) self.orig_annot = list(zip(*annot_tuples)) words = [w.orth_ for w in tokens] for i, gold_i in enumerate(self.cand_to_gold): if words[i].isspace(): self.tags[i] = 'SP' self.heads[i] = None self.labels[i] = None self.ner[i] = 'O' if gold_i is None: pass else: self.tags[i] = annot_tuples[2][gold_i] self.heads[i] = self.gold_to_cand[annot_tuples[3][gold_i]] self.labels[i] = annot_tuples[4][gold_i] self.ner[i] = annot_tuples[5][gold_i] cycle = nonproj.contains_cycle(self.heads) if cycle != None: raise Exception("Cycle found: %s" % cycle) if make_projective: proj_heads,_ = nonproj.PseudoProjectivity.projectivize(self.heads,self.labels) self.heads = proj_heads self.brackets = {} for (gold_start, gold_end, label_str) in brackets: start = self.gold_to_cand[gold_start] end = self.gold_to_cand[gold_end] if start is not None and end is not None: self.brackets.setdefault(start, {}).setdefault(end, set()) self.brackets[end][start].add(label_str) def __len__(self): return self.length @property def is_projective(self): return not nonproj.is_nonproj_tree(self.heads) def is_punct_label(label): return label == 'P' or label.lower() == 'punct'