Triple

T29007447
Position Surface form Disambiguated ID Type / Status
Subject Tony Parsons E736473 entity
Predicate notableWork P4 FINISHED
Object The Hanging Club
The Hanging Club is a crime thriller novel by British author Tony Parsons, featuring detective Max Wolfe as he investigates a vigilante group targeting unpunished criminals in London.
E1845169 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 Hanging Club | Statement: [Tony Parsons, notableWork, The Hanging Club]
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 Hanging Club
Triple: [Tony Parsons, notableWork, The Hanging Club]
Generated description
The Hanging Club is a crime thriller novel by British author Tony Parsons, featuring detective Max Wolfe as he investigates a vigilante group targeting unpunished criminals in London.

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_69f077eb81e88190ad9ff62cbb9f555e completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65fd9cb788190beb90acc39f381b1 completed May 2, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505c7863481909f74b2b808801675 completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a250a57374481909af187554d7a82fc completed June 7, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a250e35cb2c81909d7632be22680434 completed June 7, 2026, 6:22 a.m.
Created at: April 28, 2026, 9:39 a.m.