Triple

T38650815
Position Surface form Disambiguated ID Type / Status
Subject Brabazon Ponsonby, 1st Earl of Bessborough E939737 entity
Predicate spouse P13 FINISHED
Object Lucy Villiers
Lucy Villiers was an 18th-century British aristocrat who became Countess of Bessborough through her marriage to Brabazon Ponsonby, 1st Earl of Bessborough.
E2281265 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: Lucy Villiers | Statement: [Brabazon Ponsonby, 1st Earl of Bessborough, spouse, Lucy Villiers]
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: Lucy Villiers
Triple: [Brabazon Ponsonby, 1st Earl of Bessborough, spouse, Lucy Villiers]
Generated description
Lucy Villiers was an 18th-century British aristocrat who became Countess of Bessborough through her marriage to Brabazon Ponsonby, 1st Earl of Bessborough.

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_69f76ede49648190a48bfe47032a05a3 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9de61488190b270c07dfa1e0ba9 completed May 7, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4205b84ba881908ea5c4ff8becc791 completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a42081d4aa081909cee15a10ab7da3f completed June 29, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a42087b26e48190a29e08c752c67fb7 completed June 29, 2026, 5:54 a.m.
Created at: May 3, 2026, 4:33 p.m.