Triple

T29446382
Position Surface form Disambiguated ID Type / Status
Subject A Chorus of Disapproval E746860 entity
Predicate hasCharacter P2308 FINISHED
Object Bridget Baines
Bridget Baines is a character in Alan Ayckbourn's comedic play "A Chorus of Disapproval," which centers on the tangled personal lives of an amateur operatic society.
E1871831 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: Bridget Baines | Statement: [A Chorus of Disapproval, hasCharacter, Bridget Baines]
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: Bridget Baines
Triple: [A Chorus of Disapproval, hasCharacter, Bridget Baines]
Generated description
Bridget Baines is a character in Alan Ayckbourn's comedic play "A Chorus of Disapproval," which centers on the tangled personal lives of an amateur operatic society.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66b2124b08190a88f01f19caee6cf completed May 2, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c0c8fdc81908ee8280d3dd58b84 completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a2611c5b05c8190bb5237a0dafb8b4f completed June 8, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_6a2615e8084c8190bf17b0d50df4d1c3 completed June 8, 2026, 1:07 a.m.
Created at: April 28, 2026, 3:28 p.m.