def test_wiki_online():
    mentions = get_wiki_mentions()
    wiki = WikipediaRelationExtraction()

    assert not wiki.extract_all_relations(mentions[0], mentions[0]).isdisjoint(
        set(
            [
                RelationType.WIKIPEDIA_CATEGORY,
                RelationType.WIKIPEDIA_REDIRECT_LINK,
                RelationType.WIKIPEDIA_BE_COMP,
            ]
        )
    )

    assert not wiki.extract_all_relations(mentions[0], mentions[1]).isdisjoint(
        set(
            [
                RelationType.WIKIPEDIA_CATEGORY,
                RelationType.WIKIPEDIA_REDIRECT_LINK,
                RelationType.WIKIPEDIA_BE_COMP,
            ]
        )
    )

    assert (
        wiki.extract_all_relations(mentions[0], mentions[2]).pop() == RelationType.NO_RELATION_FOUND
    )
def run_example():
    logger.info("Running relation extraction example......")
    computed = ComputedRelationExtraction()
    ref_dict = ReferentDictRelationExtraction(
        ref_dict=str(LIBRARY_ROOT / "datasets" / "coref.dict1.tsv"))
    vo = VerboceanRelationExtraction(
        vo_file=str(LIBRARY_ROOT / "datasets" /
                    "verbocean.unrefined.2004-05-20.txt"))
    wiki = WikipediaRelationExtraction()
    wn = WordnetRelationExtraction()
    embed = WordEmbeddingRelationExtraction(method=EmbeddingMethod.ELMO)

    mention_x1 = MentionDataLight(
        "IBM",
        mention_context=
        "IBM manufactures and markets computer hardware, middleware and software",
    )
    mention_y1 = MentionDataLight(
        "International Business Machines",
        mention_context="International Business Machines Corporation is an "
        "American multinational information technology company",
    )

    computed_relations = computed.extract_all_relations(mention_x1, mention_y1)
    ref_dict_relations = ref_dict.extract_all_relations(mention_x1, mention_y1)
    vo_relations = vo.extract_all_relations(mention_x1, mention_y1)
    wiki_relations = wiki.extract_all_relations(mention_x1, mention_y1)
    embed_relations = embed.extract_all_relations(mention_x1, mention_y1)
    wn_relaions = wn.extract_all_relations(mention_x1, mention_y1)

    if RelationType.NO_RELATION_FOUND in computed_relations:
        logger.info("No Computed relation found")
    else:
        logger.info("Found Computed relations-%s",
                    str(list(computed_relations)))

    if RelationType.NO_RELATION_FOUND in ref_dict_relations:
        logger.info("No Referent-Dict relation found")
    else:
        logger.info("Found Referent-Dict relations-%s",
                    str(list(ref_dict_relations)))

    if RelationType.NO_RELATION_FOUND in vo_relations:
        logger.info("No Verb-Ocean relation found")
    else:
        logger.info("Found Verb-Ocean relations-%s", str(list(vo_relations)))

    if RelationType.NO_RELATION_FOUND in wiki_relations:
        logger.info("No Wikipedia relation found")
    else:
        logger.info("Found Wikipedia relations-%s", str(wiki_relations))
    if RelationType.NO_RELATION_FOUND in embed_relations:
        logger.info("No Embedded relation found")
    else:
        logger.info("Found Embedded relations-%s", str(list(embed_relations)))
    if RelationType.NO_RELATION_FOUND in wn_relaions:
        logger.info("No Wordnet relation found")
    else:
        logger.info("Found Wordnet relations-%s", str(wn_relaions))