Loading srl.py +13 −9 Original line number Diff line number Diff line Loading @@ -43,7 +43,8 @@ def ner(t): sent = pd.read_csv('data/sent_df.csv') sent = sent[sent.s.apply(crude_ner) == True] data = sent[:] #print([i for i in sent.index if i > 1400]) data = sent.iloc[1449:] srl_pred = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/srl-model-2018.05.25.tar.gz") allen_ner = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/ner-model-2018.12.18.tar.gz") Loading @@ -67,7 +68,9 @@ for i,r in data.iterrows(): names = persons[persons.w.apply(crude_ner) == True].copy() #print('names', names) verbs = names.set_index(['w']).iloc[:,1:].copy().stack().reset_index(level=1, name='arg').rename(columns={'level_1':'verb'}) verbs = names.set_index(['w']).iloc[:,1:] if not verbs.empty: verbs = verbs.copy().stack().reset_index(level=1, name='arg').rename(columns={'level_1':'verb'}) #print('verbs', verbs) verbs = verbs.replace({'O':None}).dropna() #print('verbs', verbs) Loading @@ -75,6 +78,7 @@ for i,r in data.iterrows(): verbs['same'] = namlabs_df.loc[verbs.index].bias.values == r.bias #print('verbs', verbs) verb_df = verb_df.append(verbs) print('Found {} verbs'.format(len(verbs))) verb_df.arg = verb_df.arg.str[2:] verb_df.to_csv('vdberg_output.csv') Loading vdberg_output.csv +2 −1 Original line number Diff line number Diff line ,arg,same,verb Clinton,ARG1,True,excoriated Obama,ARG1,False,freaking Obama,ARGM-DIR,False,move Loading
srl.py +13 −9 Original line number Diff line number Diff line Loading @@ -43,7 +43,8 @@ def ner(t): sent = pd.read_csv('data/sent_df.csv') sent = sent[sent.s.apply(crude_ner) == True] data = sent[:] #print([i for i in sent.index if i > 1400]) data = sent.iloc[1449:] srl_pred = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/srl-model-2018.05.25.tar.gz") allen_ner = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/ner-model-2018.12.18.tar.gz") Loading @@ -67,7 +68,9 @@ for i,r in data.iterrows(): names = persons[persons.w.apply(crude_ner) == True].copy() #print('names', names) verbs = names.set_index(['w']).iloc[:,1:].copy().stack().reset_index(level=1, name='arg').rename(columns={'level_1':'verb'}) verbs = names.set_index(['w']).iloc[:,1:] if not verbs.empty: verbs = verbs.copy().stack().reset_index(level=1, name='arg').rename(columns={'level_1':'verb'}) #print('verbs', verbs) verbs = verbs.replace({'O':None}).dropna() #print('verbs', verbs) Loading @@ -75,6 +78,7 @@ for i,r in data.iterrows(): verbs['same'] = namlabs_df.loc[verbs.index].bias.values == r.bias #print('verbs', verbs) verb_df = verb_df.append(verbs) print('Found {} verbs'.format(len(verbs))) verb_df.arg = verb_df.arg.str[2:] verb_df.to_csv('vdberg_output.csv') Loading
vdberg_output.csv +2 −1 Original line number Diff line number Diff line ,arg,same,verb Clinton,ARG1,True,excoriated Obama,ARG1,False,freaking Obama,ARGM-DIR,False,move