Triple

T24284470
Position Surface form Disambiguated ID Type / Status
Subject Hero the Hedgehog E605633 entity
Predicate creator P184 FINISHED
Object London 2017 organising committee
The London 2017 organising committee was the body responsible for planning and delivering the 2017 World Championships in Athletics and related events in London.
 E1629311 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: London 2017 organising committee | Statement: [Hero the Hedgehog, creator, London 2017 organising committee]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: London 2017 organising committee
Triple: [Hero the Hedgehog, creator, London 2017 organising committee]
Generated description
The London 2017 organising committee was the body responsible for planning and delivering the 2017 World Championships in Athletics and related events in London.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e295480d0c8190846fc3c2e2da1d4c completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28f54c5948190a28207d47d6205e4 completed April 29, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9c8b1f88190a63dfe17c6d41159 completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fcdabbd488190b5fd6ea22494e941 completed May 22, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_6a0fce302f6081909a462e08d08c5bb7 completed May 22, 2026, 3:32 a.m.
Created at: April 18, 2026, 12:08 a.m.