| from nltk.stem import WordNetLemmatizer |
| lemma = WordNetLemmatizer().lemmatize |
| import nltk |
| pos_tag = nltk.pos_tag |
| from nltk.corpus import stopwords |
| import sys |
|
|
| mode = sys.argv[1] |
| file_dir = "./WritingPrompts/ini_data/" if "w" in mode else "./ROCStories/ini_data/" |
| file_name = "train.wp_target" if "w" in mode else "train.txt" |
|
|
| def get_avail_phrases(): |
| sw = set(stopwords.words('english')) |
| avail_phrases = set() |
| fin = open("./conceptnet_entity.csv", 'r') |
| for i, line in enumerate(fin): |
| avail_phrases.add(' '.join(line.strip().split("|||")[:-1])) |
| avail_phrases = avail_phrases - sw |
| fin.close() |
|
|
| fin = open("./negation.txt", 'r') |
| for i, line in enumerate(fin): |
| avail_phrases.add(' '.join(line.strip().split()[1:])) |
| fin.close() |
|
|
| for w in [".", ",", "!", "?", "male", "female", "neutral"]: |
| avail_phrases.add(w) |
|
|
| return avail_phrases |
|
|
| avail_phrases = get_avail_phrases() |
|
|
| vocab = {} |
| with open("%s/%s"%(file_dir, file_name), "r") as fin1: |
| for kkk, line in enumerate(fin1): |
| if kkk % 1000 == 0: |
| print(kkk) |
| tmp = line.strip().split() |
| pos = pos_tag(tmp) |
| for word_pos in pos: |
| if lemma(word_pos[0], 'v' if word_pos[1][0] == 'V' else 'n') not in avail_phrases: |
| continue |
| if word_pos[0] in vocab: |
| vocab[word_pos[0]]["number"] += 1 |
| if word_pos[1] in vocab[word_pos[0]]: |
| vocab[word_pos[0]][word_pos[1]] += 1 |
| else: |
| vocab[word_pos[0]][word_pos[1]] = 1 |
| else: |
| vocab[word_pos[0]] = {word_pos[1]:1, "number":1} |
| vocab_list = sorted(vocab, key=lambda x: vocab[x]["number"], reverse=True) |
| with open("%s/entity_vocab.txt"%file_dir, "w") as fout: |
| for v in vocab_list: |
| pos_list = sorted(vocab[v], key=vocab[v].get, reverse=True) |
| pos_list.remove("number") |
| fout.write("%s %d|||"%(v, vocab[v]["number"]) + "|||".join(["%s %d"%(p, vocab[v][p]) for p in pos_list]) + "\n") |
