Triple

T25011536
Position Surface form Disambiguated ID Type / Status
Subject Battle Hill E625999 entity
Predicate governingBody P46 FINISHED
Object North Tyneside Council
North Tyneside Council is the local authority responsible for providing municipal services and governance across the Metropolitan Borough of North Tyneside in Tyne and Wear, England.
E158416 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: North Tyneside Council | Statement: [Battle Hill, governingBody, North Tyneside Council]
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: North Tyneside Council
Triple: [Battle Hill, governingBody, North Tyneside Council]
Generated description
North Tyneside Council is the local authority responsible for providing municipal services and governance across the Metropolitan Borough of North Tyneside in Tyne and Wear, England.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44ba10d40819093e1906bd928b3f0 completed May 1, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a122966816c8190bdd3a97dd4096d97 completed May 23, 2026, 10:25 p.m.
NEDg Description generation batch_6a122a3a3b3c8190ab41feb5652546bb completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122add10688190aa06ce1d690c1867 completed May 23, 2026, 10:31 p.m.
Created at: April 18, 2026, 6:05 a.m.