Triple

T27269712
Position Surface form Disambiguated ID Type / Status
Subject Westfield, Indiana E688013 entity
Predicate hasMajorFacility P105 FINISHED
Object Grand Park Sports Campus
Grand Park Sports Campus is a large multi-sport complex in Westfield, Indiana, known for its extensive fields and facilities that host youth and amateur sporting events and tournaments.
E1762998 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: Grand Park Sports Campus | Statement: [Westfield, Indiana, hasMajorFacility, Grand Park Sports Campus]
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: Grand Park Sports Campus
Triple: [Westfield, Indiana, hasMajorFacility, Grand Park Sports Campus]
Generated description
Grand Park Sports Campus is a large multi-sport complex in Westfield, Indiana, known for its extensive fields and facilities that host youth and amateur sporting events and tournaments.

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_69ef3558cf8881909595ef89daf6e14a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6272167c481909ca7783afdf7e14e completed May 2, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12628b6a148190879f74e1ac22ffc8 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1266920d008190b029acd1c8efc214 completed May 24, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1266f0b7448190a158f776016efacd completed May 24, 2026, 2:48 a.m.
Created at: April 27, 2026, 10:58 a.m.