Triple

T25184960
Position Surface form Disambiguated ID Type / Status
Subject Jenner Park Stadium E630693 entity
Predicate namedAfter P63 FINISHED
Object Jenner Park
Jenner Park is a district and residential area in Barry, Vale of Glamorgan, Wales, best known for giving its name to the local football ground, Jenner Park Stadium.
E2120634 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: Jenner Park | Statement: [Jenner Park Stadium, namedAfter, Jenner Park]
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: Jenner Park
Triple: [Jenner Park Stadium, namedAfter, Jenner Park]
Generated description
Jenner Park is a district and residential area in Barry, Vale of Glamorgan, Wales, best known for giving its name to the local football ground, Jenner Park Stadium.

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_69e75a88fdf081908e47ae6e195c14e1 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46dc9e8fc8190844984493b19b9b1 completed May 1, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37b248b6d8819083d6f2d1ecac346d completed June 21, 2026, 9:43 a.m.
NEDg Description generation batch_6a37b44d33708190bf09f5667351e546 completed June 21, 2026, 9:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37b4aaf3b081909f052e9cdbfd5996 completed June 21, 2026, 9:53 a.m.
Created at: April 21, 2026, 12:37 p.m.