sigir2018-kg-contextualization

This repository contains the data with manual annotations gathered using CrowdFlower for our SIGIR 2018 paper:

Nikos Voskarides, Edgar Meij, Ridho Reinanda, Abhinav Khaitan, Miles Osborne, Giorgio Stefanoni, Kambadur Prabhanjan and Maarten de Rijke: Weakly-supervised Contextualization of Knowledge Graph Facts. 2018. In Proceedings of the 41st International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR '18).

It based on Freebase and released under the same CC-BY license. We provide more details on this dataset at https://www.techatbloomberg.com/research-weakly-supervised-contextualization-knowledge-graph-facts/.

The file itself is gzipped and has the following structure.

{
    "query_id" : {
        "relation": "",
        "query": "",
        "candidates": [
            {
                "cand_id": {
                    "cf_label": 0,
                    "dist_sup_label": 0,
                    "path": []
                }
            }
        ]
    }
}

Field Description

relation The predicates of the query relation

query The query fact path

candidates The list of candidate facts

cand_id The candidate fact ID

cf_label The relevance label from CrowdFlower annotations

dist_sup_label The relevance label from distant supervision

path The candidate fact path: ([subject_id, list_of_subject_types], pred, [object_id, list_of_object_types])

Note that the format of each path is as follows.

Field Description

subject_id The subject ID

subject_type_1...n The types of the subject

predicate The predicate

object_id The object ID

object_type_1...n The types of the object