f1fc699be9ce8b249cf5bd670d2200f990a5294d,conceptnet5/vectors/evaluation/analogy.py,,eval_analogies,#Any#,85

Before Change

        standardized_uri("en", word)
        for word in wordfreq.top_n_list("en", 100000)
    ]
    tframe = frame.loc[vocab]
    total = 0
    correct = 0
    for quad in quads:
        if all(term in tframe.index for term in quad):
            prompt = quad[:3]
            answer = quad[3]
            vector = analogy_func(frame, *prompt)
            similar = similar_to_vec(tframe, vector)
            result = None
            for match in similar.index:
                if match not in prompt:
                    result = match
                    break
            if result == answer:
                correct += 1
            else:
                print(
                    "%s : %s :: %s : %s (should be %s)"
                    % (quad[0], quad[1], quad[2], result.upper(), answer)
                    )
            total += 1
    return correct, total, correct / total

After Change

        standardized_uri("en", word)
        for word in wordfreq.top_n_list("en", 200000)
    ]
    wrap = VectorSpaceWrapper(frame=frame)
    vecs = np.vstack([wrap.get_vector(word) for word in vocab])
    tframe = pd.DataFrame(vecs, index=vocab)
    total = 0
    correct = 0
    seen_mistakes = set()

Instances