Triple

T35255121
Position Surface form Disambiguated ID Type / Status
Subject Hatfield Woodhouse E1018209 entity
Predicate hasPrimarySchool P3445 FINISHED
Object Hatfield Woodhouse Primary School
Hatfield Woodhouse Primary School is a local primary education institution serving young children in the village of Hatfield Woodhouse, South Yorkshire, England.
E2132247 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: Hatfield Woodhouse Primary School | Statement: [Hatfield Woodhouse, hasPrimarySchool, Hatfield Woodhouse 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: Hatfield Woodhouse Primary School
Triple: [Hatfield Woodhouse, hasPrimarySchool, Hatfield Woodhouse Primary School]
Generated description
Hatfield Woodhouse Primary School is a local primary education institution serving young children in the village of Hatfield Woodhouse, South 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_69f76de407d081909dfc3c419817ae93 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f6506b88190ab3bb77388b93845 completed May 3, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380fb25e888190a6bb76576545dfb0 completed June 21, 2026, 4:22 p.m.
NEDg Description generation batch_6a38101fde60819092808d5adde771c9 completed June 21, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a3811120ca48190a47a45c2e306b1a8 completed June 21, 2026, 4:28 p.m.
Created at: May 3, 2026, 4:02 p.m.