Triple

T31565548
Position Surface form Disambiguated ID Type / Status
Subject Danby, North Yorkshire E805401 entity
Predicate hasEstate P8997 FINISHED
Object Danby Estate
Danby Estate is a historic rural property in North Yorkshire, England, known for its moorland landscapes, traditional farming, and role within the North York Moors National Park.
E1966419 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: Danby Estate | Statement: [Danby, North Yorkshire, hasEstate, Danby Estate]
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: Danby Estate
Triple: [Danby, North Yorkshire, hasEstate, Danby Estate]
Generated description
Danby Estate is a historic rural property in North Yorkshire, England, known for its moorland landscapes, traditional farming, and role within the North York Moors National Park.

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_69f348d2ee94819091918d1789398c29 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a7e275fc8190988d89edd5d46c68 completed May 3, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d9958648190ac665cda29576a2c completed June 11, 2026, 9:50 p.m.
NEDg Description generation batch_6a2b2e47364c81908ec9999f916a476c completed June 11, 2026, 9:53 p.m.
NED2 Entity disambiguation (via description) batch_6a2b2f18ca908190a8a73b4f21bbc78a completed June 11, 2026, 9:56 p.m.
Created at: April 30, 2026, 10:17 p.m.