Triple

T30575101
Position Surface form Disambiguated ID Type / Status
Subject Sir William Pynsent, 1st Baronet E778222 entity
Predicate residence P75 FINISHED
Object Burton Pynsent
Burton Pynsent is a historic country estate in Somerset, England, best known for its association with Sir William Pynsent and the prominent Pynsent family.
E1923484 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: Burton Pynsent | Statement: [Sir William Pynsent, 1st Baronet, residence, Burton Pynsent]
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: Burton Pynsent
Triple: [Sir William Pynsent, 1st Baronet, residence, Burton Pynsent]
Generated description
Burton Pynsent is a historic country estate in Somerset, England, best known for its association with Sir William Pynsent and the prominent Pynsent family.

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_69f2249f8c148190ae7eb3912cde112a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6893cedbc8190af12752ccae5e062 completed May 2, 2026, 11:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2863ce9e448190a7393c370b06f96f completed June 9, 2026, 7:04 p.m.
NEDg Description generation batch_6a2867f80e2c81909ea8c4da72eb9753 completed June 9, 2026, 7:22 p.m.
NED2 Entity disambiguation (via description) batch_6a286885f2cc8190bc4de1e4f7239f4e completed June 9, 2026, 7:24 p.m.
Created at: April 29, 2026, 8:22 p.m.