Triple

T35877762
Position Surface form Disambiguated ID Type / Status
Subject Marion Taylor E1037414 entity
Predicate appearsIn P795 FINISHED
Object My Policeman (novel)
*My Policeman* is a 2012 novel by Bethan Roberts that explores a tragic love triangle in 1950s Brighton between a married couple and the husband’s male lover, examining repression, desire, and the costs of societal homophobia.
 E283089 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: My Policeman (novel) | Statement: [Marion Taylor, appearsIn, My Policeman (novel)]
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: My Policeman (novel)
Triple: [Marion Taylor, appearsIn, My Policeman (novel)]
Generated description
*My Policeman* is a 2012 novel by Bethan Roberts that explores a tragic love triangle in 1950s Brighton between a married couple and the husband’s male lover, examining repression, desire, and the costs of societal homophobia.

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_69f76e1e701c8190a4990d4978ce4fe6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa000d808190b0f54e755ee9dae3 completed May 3, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae214e1481908a4b367dcf0a0f11 completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38af26a6088190956c385283dfcef6 completed June 22, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_6a38afcce12c8190ba69d9dc33f5a8d7 completed June 22, 2026, 3:45 a.m.
Created at: May 3, 2026, 4:06 p.m.