Triple

T28894573
Position Surface form Disambiguated ID Type / Status
Subject Bewley E732804 entity
Predicate hasNotableBearer P458 FINISHED
Object Shane Bewley
Shane Bewley is an individual notable enough to be recognized as a bearer of the surname Bewley, though specific widely known public details about him are not readily available.
E1841142 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: Shane Bewley | Statement: [Bewley, hasNotableBearer, Shane Bewley]
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: Shane Bewley
Triple: [Bewley, hasNotableBearer, Shane Bewley]
Generated description
Shane Bewley is an individual notable enough to be recognized as a bearer of the surname Bewley, though specific widely known public details about him are not readily available.

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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65aa2c5fc8190a74ea45c30e714d4 completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec32deb8819095cae7528baed53e completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f3f8f338819091246a60c657e8c3 completed June 7, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a24f418018081908f81e51f8c5a68e8 completed June 7, 2026, 4:31 a.m.
Created at: April 28, 2026, 7:58 a.m.