Triple

T33851809
Position Surface form Disambiguated ID Type / Status
Subject Billy Bevan E867644 entity
Predicate birthName P65 FINISHED
Object William Bevan Harris
William Bevan Harris, better known by his stage name Billy Bevan, was an Australian-born silent film comedian and character actor who became a familiar face in early Hollywood comedies.
E2071882 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: William Bevan Harris | Statement: [Billy Bevan, birthName, William Bevan Harris]
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: William Bevan Harris
Triple: [Billy Bevan, birthName, William Bevan Harris]
Generated description
William Bevan Harris, better known by his stage name Billy Bevan, was an Australian-born silent film comedian and character actor who became a familiar face in early Hollywood comedies.

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_69f349937b648190a34ada70f6a2b534 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70073e67c8190aa5b578cafed96db completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a367615433c819092dd79294b683ebe completed June 20, 2026, 11:14 a.m.
NEDg Description generation batch_6a3676bcd1c48190be60af977f59ab1c completed June 20, 2026, 11:17 a.m.
NED2 Entity disambiguation (via description) batch_6a367856f37c8190a4ff255c3590592e completed June 20, 2026, 11:24 a.m.
Created at: May 1, 2026, 1:47 a.m.