Triple

T36043289
Position Surface form Disambiguated ID Type / Status
Subject Crazyhead E1042599 entity
Predicate castMember P1668 FINISHED
Object Lewis Reeves
Lewis Reeves is a British actor known for his work in television, film, and theatre, including roles in series like Crazyhead.
E2184770 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: Lewis Reeves | Statement: [Crazyhead, castMember, Lewis Reeves]
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: Lewis Reeves
Triple: [Crazyhead, castMember, Lewis Reeves]
Generated description
Lewis Reeves is a British actor known for his work in television, film, and theatre, including roles in series like Crazyhead.

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_69f76e2d7e8c8190bac4e90734566799 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b1c1fc708190b9238de53a28b189 completed May 3, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39cfb0358c8190a05555a4ee81314a completed June 23, 2026, 12:13 a.m.
NEDg Description generation batch_6a39d0973c4481909e3c41c76fe0461b completed June 23, 2026, 12:17 a.m.
NED2 Entity disambiguation (via description) batch_6a39d149d0c88190b232b80550967869 completed June 23, 2026, 12:20 a.m.
Created at: May 3, 2026, 4:07 p.m.