Triple

T31228201
Position Surface form Disambiguated ID Type / Status
Subject Leslie Browne E796200 entity
Predicate hasRelative P367 FINISHED
Object Elizabeth Browne
Elizabeth Browne is a member of the Browne family, related to American ballet dancer and actress Leslie Browne.
E864878 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: Elizabeth Browne | Statement: [Leslie Browne, hasRelative, Elizabeth Browne]
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: Elizabeth Browne
Triple: [Leslie Browne, hasRelative, Elizabeth Browne]
Generated description
Elizabeth Browne is a member of the Browne family, related to American ballet dancer and actress Leslie Browne.

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_69f224da98f88190ab32f690cce5d303 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69c532354819092d9d8247548c6a2 completed May 3, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29593457588190bf8f549bc2666dd6 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295d01b09c8190a87c2ed99d745566 completed June 10, 2026, 12:48 p.m.
NED2 Entity disambiguation (via description) batch_6a2960ee531881908fe084e5dd959317 completed June 10, 2026, 1:04 p.m.
Created at: April 29, 2026, 9:10 p.m.