Triple

T24577007
Position Surface form Disambiguated ID Type / Status
Subject Copthall Playing Fields E608138 entity
Predicate partOf P40 FINISHED
Object Copthall sports complex
Copthall sports complex is a large multi-sport and leisure facility in Mill Hill, London, featuring extensive playing fields, athletics tracks, and various indoor and outdoor sports amenities.
E1641885 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: Copthall sports complex | Statement: [Copthall Playing Fields, partOf, Copthall sports complex]
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: Copthall sports complex
Triple: [Copthall Playing Fields, partOf, Copthall sports complex]
Generated description
Copthall sports complex is a large multi-sport and leisure facility in Mill Hill, London, featuring extensive playing fields, athletics tracks, and various indoor and outdoor sports amenities.

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_69e2c4cdab6c8190aae6e5d3de55c95e completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a9295ab08190b6c137c99bcd958f completed April 30, 2026, 12:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0ff870efa081909cd33308e13258b9 completed May 22, 2026, 6:32 a.m.
NEDg Description generation batch_6a0ff96d423881908d81db0b6bc78921 completed May 22, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a0ffa8bb5208190b473d834c40e7ef3 completed May 22, 2026, 6:41 a.m.
Created at: April 18, 2026, 2:29 a.m.