Triple

T30665674
Position Surface form Disambiguated ID Type / Status
Subject Ingleby Barwick E780653 entity
Predicate hasPrimarySchool P3445 FINISHED
Object Barley Fields Primary School
Barley Fields Primary School is a local primary education institution serving the community of Ingleby Barwick in North Yorkshire, England.
E1926503 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: Barley Fields Primary School | Statement: [Ingleby Barwick, hasPrimarySchool, Barley Fields Primary School]
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: Barley Fields Primary School
Triple: [Ingleby Barwick, hasPrimarySchool, Barley Fields Primary School]
Generated description
Barley Fields Primary School is a local primary education institution serving the community of Ingleby Barwick in North Yorkshire, 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_69f224a6d10481909290be1a00fc83b3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68ae41860819084f56b1c66e2721f completed May 2, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2870f828388190a642cbd3f6f4b5e9 completed June 9, 2026, 8 p.m.
NEDg Description generation batch_6a28765d87c48190a4cd6b1d5dabfeca completed June 9, 2026, 8:23 p.m.
NED2 Entity disambiguation (via description) batch_6a2876c040148190ac660dcab205d9e1 completed June 9, 2026, 8:25 p.m.
Created at: April 29, 2026, 8:31 p.m.