Triple

T31735165
Position Surface form Disambiguated ID Type / Status
Subject The Complaints E809973 entity
Predicate characterRole P268 FINISHED
Object Malcolm Fox is a Detective Inspector
Malcolm Fox is a principled but often conflicted Detective Inspector in Ian Rankin’s crime novels, known for investigating police misconduct within the Professional Standards unit.
E1976597 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: Malcolm Fox is a Detective Inspector | Statement: [The Complaints, characterRole, Malcolm Fox is a Detective Inspector]
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: Malcolm Fox is a Detective Inspector
Triple: [The Complaints, characterRole, Malcolm Fox is a Detective Inspector]
Generated description
Malcolm Fox is a principled but often conflicted Detective Inspector in Ian Rankin’s crime novels, known for investigating police misconduct within the Professional Standards unit.

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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ab22f464819098766f11b1c3c846 completed May 3, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b947956648190badb026e05af1999 completed June 12, 2026, 5:09 a.m.
NEDg Description generation batch_6a2b951b5f0c8190b05974307ab529d0 completed June 12, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_6a2b95bb5bfc81908740d2f57f30e914 completed June 12, 2026, 5:14 a.m.
Created at: April 30, 2026, 11:23 p.m.