Triple

T32499583
Position Surface form Disambiguated ID Type / Status
Subject Aubrey de Vere, 20th Earl of Oxford E830616 entity
Predicate mother P120 FINISHED
Object Henrietta Tracy
Henrietta Tracy was an English noblewoman best known as the mother of Aubrey de Vere, 20th Earl of Oxford, a prominent peer in the English aristocracy.
E2010309 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: Henrietta Tracy | Statement: [Aubrey de Vere, 20th Earl of Oxford, mother, Henrietta Tracy]
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: Henrietta Tracy
Triple: [Aubrey de Vere, 20th Earl of Oxford, mother, Henrietta Tracy]
Generated description
Henrietta Tracy was an English noblewoman best known as the mother of Aubrey de Vere, 20th Earl of Oxford, a prominent peer in the English aristocracy.

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_69f349219cb8819087e120f509629c1b completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c442b4d88190a00e9781206b0520 completed May 3, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347058807881908b47c8eb8840d4c1 completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a3471e541888190b41a9562c7d29278 completed June 18, 2026, 10:32 p.m.
NED2 Entity disambiguation (via description) batch_6a347293cdf08190bbc8ce521ded677c completed June 18, 2026, 10:34 p.m.
Created at: May 1, 2026, 12:59 a.m.