Triple

T33265422
Position Surface form Disambiguated ID Type / Status
Subject Clifford E851630 entity
Predicate hasConservationArea P855 FINISHED
Object Clifford Conservation Area
Clifford Conservation Area is a protected natural and scenic landscape in and around the village of Clifford, designated to preserve its historic rural character and local biodiversity.
 E2044353 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: Clifford Conservation Area | Statement: [Clifford, hasConservationArea, Clifford Conservation Area]
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: Clifford Conservation Area
Triple: [Clifford, hasConservationArea, Clifford Conservation Area]
Generated description
Clifford Conservation Area is a protected natural and scenic landscape in and around the village of Clifford, designated to preserve its historic rural character and local biodiversity.

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_69f349642dac81908a37ffcc3b976a55 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de2054d48190ac3f06c6203a5f2f completed May 3, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35391c568081908e1821cea63d906f completed June 19, 2026, 12:42 p.m.
NEDg Description generation batch_6a353992e2c48190b777313293290bad completed June 19, 2026, 12:44 p.m.
NED2 Entity disambiguation (via description) batch_6a353a48a0e08190bbd5d55a8bd390ae completed June 19, 2026, 12:47 p.m.
Created at: May 1, 2026, 1:32 a.m.