Triple

T35360987
Position Surface form Disambiguated ID Type / Status
Subject Edge of Fear E1021479 entity
Predicate starring P1507 FINISHED
Object Chiké Okonkwo
Chiké Okonkwo is a British-Nigerian actor known for his work in film, television, and theatre, including roles in projects such as "Edge of Fear" and the TV series "La Brea."
E2136406 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: Chiké Okonkwo | Statement: [Edge of Fear, starring, Chiké Okonkwo]
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: Chiké Okonkwo
Triple: [Edge of Fear, starring, Chiké Okonkwo]
Generated description
Chiké Okonkwo is a British-Nigerian actor known for his work in film, television, and theatre, including roles in projects such as "Edge of Fear" and the TV series "La Brea."

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_69f76def44c881908a20e8008572eb44 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f791ce211c8190aef1c7ec9b3ce68a completed May 3, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3823db96fc819084883c17cf0fd3fd completed June 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a382496eb30819081ec6e3c0f8c7137 completed June 21, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_6a3825d213688190aefa08d3d21f6b75 completed June 21, 2026, 5:56 p.m.
Created at: May 3, 2026, 4:03 p.m.