nordlys.logic.el.ltr module¶

LTR Entity Linking Approach¶

Class for Learning-to-Rank entity linking approach

Author:	Faegheh Hasibi

class nordlys.logic.el.ltr.LTR(query, entity, elastic, fcache, model=None, threshold=None, cmns_th=0.1)[source]¶

static gen_train_set(gt, query_file, train_set)[source]¶: Trains LTR model for entity linking.

get_candidate_inss()[source]¶

Detects mentions and their candidate entities (with their commoness scores) and generates instances

Returns:	Instances object

get_features(ins, cand_ens=None)[source]¶

Generates the features set for each instance.

Parameters:	ins – instance object cand_ens – dictionary of candidate entities {en_id: cmns, …}
Returns:	dictionary of features {ftr_name: value, …}

Links the query to the entity.

Returns:	dictionary [{“mention”: xx, “entity”: yy, “score”: zz}, …]

static load_yerd(gt_file)[source]¶

Reads the Y-ERD collection and returns a dictionary.

Parameters:	gt_file – Path to the Y-ERD collection
Returns:	dictionary {(qid, query, en_id, mention) …}

rank_ens()[source]¶

Ranks instances according to the learned LTR model

Parameters:	n – length of n-gram
Returns:	dictionary {(dbp_uri, fb_id):commonness, ..}