Triple

T25085818
Position Surface form Disambiguated ID Type / Status
Subject Gerald Scales E628316 entity
Predicate appearsIn P795 FINISHED
Object The Old Wives’ Tale
The Old Wives’ Tale is a 1908 novel by Arnold Bennett that traces the contrasting lives of two sisters from a Staffordshire drapery shop through marriage, separation, and old age, offering a rich, realistic portrait of provincial and Parisian life.
E159428 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: The Old Wives’ Tale | Statement: [Gerald Scales, appearsIn, The Old Wives’ Tale]
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: The Old Wives’ Tale
Triple: [Gerald Scales, appearsIn, The Old Wives’ Tale]
Generated description
The Old Wives’ Tale is a 1908 novel by Arnold Bennett that traces the contrasting lives of two sisters from a Staffordshire drapery shop through marriage, separation, and old age, offering a rich, realistic portrait of provincial and Parisian life.

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_69e2ff2f58e881908340527bc5d34f07 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f461e3bef081908ef1c4d28cfe03e1 completed May 1, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad3714788190abbc5ead47b2bd09 completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10ae56b8a48190a448e1a4bd938a2b completed May 22, 2026, 7:28 p.m.
NED2 Entity disambiguation (via description) batch_6a10af45b9048190b1613ef21fa00caf completed May 22, 2026, 7:32 p.m.
Created at: April 18, 2026, 6:23 a.m.