Triple

T27904650
Position Surface form Disambiguated ID Type / Status
Subject Greville Janner E705732 entity
Predicate givenName P17 FINISHED
Object Greville
Greville is a masculine given name of English origin, historically associated with British aristocracy and public figures.
E1793985 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: Greville | Statement: [Greville Janner, givenName, Greville]
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: Greville
Triple: [Greville Janner, givenName, Greville]
Generated description
Greville is a masculine given name of English origin, historically associated with British aristocracy and public figures.

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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f639fc02148190b67402ee8c312000 completed May 2, 2026, 5:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a130369d0fc81909b4b2b1933440ed0 completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a1304d193f48190a19d6adbf3542088 completed May 24, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_6a13057d68408190bb5e5855121f5195 completed May 24, 2026, 2:04 p.m.
Created at: April 27, 2026, 6:44 p.m.