Triple

T34565945
Position Surface form Disambiguated ID Type / Status
Subject Bill Williams E887481 entity
Predicate alsoKnownAs P39 FINISHED
Object Bill MacWilliams
Bill MacWilliams is an individual known primarily as an alternate or professional name used by Bill Williams.
E2104095 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: Bill MacWilliams | Statement: [Bill Williams, alsoKnownAs, Bill MacWilliams]
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: Bill MacWilliams
Triple: [Bill Williams, alsoKnownAs, Bill MacWilliams]
Generated description
Bill MacWilliams is an individual known primarily as an alternate or professional name used by Bill Williams.

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_69f349d0c4d881908dd0950f5eb9ec0a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72065f4988190931aac5d785e7f64 completed May 3, 2026, 10:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a374100d73881908095a23a3032f589 completed June 21, 2026, 1:40 a.m.
NEDg Description generation batch_6a374208897081909434c3a2e34d2d2f completed June 21, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a3743223b3881909db5005278415166 completed June 21, 2026, 1:49 a.m.
Created at: May 1, 2026, 2:02 a.m.