Triple

T29920301
Position Surface form Disambiguated ID Type / Status
Subject Elleston Trevor E759908 entity
Predicate usedPseudonym P3799 FINISHED
Object Mansell Black
Mansell Black is a pseudonym used by British novelist Elleston Trevor, known for his thrillers and adventure stories.
E1891061 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: Mansell Black | Statement: [Elleston Trevor, usedPseudonym, Mansell Black]
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: Mansell Black
Triple: [Elleston Trevor, usedPseudonym, Mansell Black]
Generated description
Mansell Black is a pseudonym used by British novelist Elleston Trevor, known for his thrillers and adventure stories.

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_69f2246189fc8190996b63ee1f9a2374 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67793b72c8190ae654ae110b82d84 completed May 2, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a271419a8ec819099d4b2ba1e6a399d completed June 8, 2026, 7:12 p.m.
NEDg Description generation batch_6a27169053048190a44f86999eb062ff completed June 8, 2026, 7:22 p.m.
NED2 Entity disambiguation (via description) batch_6a27174286f4819084d41fe4ebde95e8 completed June 8, 2026, 7:25 p.m.
Created at: April 29, 2026, 6:14 p.m.