Triple

T38306277
Position Surface form Disambiguated ID Type / Status
Subject Brigg and Cleethorpes E1032352 entity
Predicate predecessorConstituency P16751 FINISHED
Object Brigg and Scunthorpe
Brigg and Scunthorpe was a former UK parliamentary constituency in Humberside that included the industrial town of Scunthorpe and the market town of Brigg.
E2267963 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: Brigg and Scunthorpe | Statement: [Brigg and Cleethorpes, predecessorConstituency, Brigg and Scunthorpe]
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: Brigg and Scunthorpe
Triple: [Brigg and Cleethorpes, predecessorConstituency, Brigg and Scunthorpe]
Generated description
Brigg and Scunthorpe was a former UK parliamentary constituency in Humberside that included the industrial town of Scunthorpe and the market town of Brigg.

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_69f76e0f2084819091299d021625c3fe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc64cd8f08190b0d2b0907596eab9 completed May 7, 2026, 5:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b290c3588190a80697fc442b0f18 completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b3aad0308190a8b1aea3b38ddc18 completed June 28, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_6a41b4ab67288190bf774036d4fe05e2 completed June 28, 2026, 11:56 p.m.
Created at: May 3, 2026, 4:30 p.m.