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test_cases_eval.py
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test_cases_eval.py
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from eval import eval_ceaf
if __name__ == "__main__":
print("================= case 1 (in the paper) =================")
golds = {
"docid1": {"Target": [["Pilmai telephone company building", "telephone company building", "telephone company offices"], ["water pipes"], ["public telephone booth"]]},
}
preds = {
"docid1": {"Target": [["water pipes"], ["Pilmai telephone company building"], ["public telephone booth"], ["telephone company offices"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("================= case 2 (in the paper) =================")
golds = {
"docid1": {"Target": [["Pilmai telephone company building", "telephone company building", "telephone company offices"], ["water pipes"], ["public telephone booth"]]},
}
preds = {
"docid1": {"Target": [["Pilmai telephone company building"], ["water pipes"], ["public telephone booth"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("================= case 3 (in the paper) =================")
golds = {
"docid1": {"Target": [["Pilmai telephone company building", "telephone company building", "telephone company offices"], ["water pipes"], ["public telephone booth"]]},
}
preds = {
"docid1": {"Target": [["Pilmai telephone company building"], ["public telephone booth"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("\n\n================= case 4 =================")
golds = {
"docid1": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
}
preds = {
"docid1": {"PerpInd": [["m4"], ["m1"], ["m5"], ["m6"], ["m3"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("================= case 5 =================")
golds = {
"docid2": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
}
preds = {
"docid2": {"PerpInd": [["m1", "m2"], ["m4"], ["m5"], ["m6"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("================= case 6 =================")
golds = {
"docid3": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
}
preds = {
"docid3": {"PerpInd": [["m1", "m2", "m3", "m4"], ["m5"], ["m6"]]},
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print
print("================= case 7 =================")
golds = {
"docid1": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
"docid2": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
"docid3": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]},
"docid4": {"PerpInd": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]],
"PerpOrg": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]],
"Target": [["m1", "m2", "m3"], ["m4"], ["m5"], ["m6"]]}
}
preds = {
"docid1": {"PerpInd": [["m4"], ["m1"], ["m5"], ["m6"], ["m3"]]},
"docid2": {"PerpInd": [["m1", "m2"], ["m4"], ["m5"], ["m6"]]},
"docid3": {"PerpInd": [["m1", "m2", "m3", "m4"], ["m5"], ["m6"]]},
"docid4": {"PerpInd": [["m4"], ["m1"], ["m5"], ["m6"], ["m3"]],
"PerpOrg": [["m1", "m2"], ["m4"], ["m5"], ["m6"]],
"Target": [["m1", "m2", "m3", "m4"], ["m5"], ["m6"]]}
}
results = eval_ceaf(preds, golds, docids=[])
print("golds", golds)
print("preds", preds)
print("phi_strict: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["strict"]["micro_avg"]["p"] * 100, results["strict"]["micro_avg"]["r"] * 100, results["strict"]["micro_avg"]["f1"] * 100))
print("phi_prop: P: {:.2f}%, R: {:.2f}%, F1: {:.2f}%".format(results["prop"]["micro_avg"]["p"] * 100, results["prop"]["micro_avg"]["r"] * 100, results["prop"]["micro_avg"]["f1"] * 100))
print