Triple

T34372297
Position Surface form Disambiguated ID Type / Status
Subject Bartholomew Bogue E882191 entity
Predicate enemyOf P437 FINISHED
Object Matthew Cullen
Matthew Cullen is a central protagonist in the 2016 Western film "The Magnificent Seven," a determined villager who seeks help from gunmen to defend his town from a ruthless industrialist.
E2096090 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: Matthew Cullen | Statement: [Bartholomew Bogue, enemyOf, Matthew Cullen]
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: Matthew Cullen
Triple: [Bartholomew Bogue, enemyOf, Matthew Cullen]
Generated description
Matthew Cullen is a central protagonist in the 2016 Western film "The Magnificent Seven," a determined villager who seeks help from gunmen to defend his town from a ruthless industrialist.

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_69f349bf5d7481908dd5da4cbdf74047 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7185163888190975562eb81431803 completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3718206f6c81908641e980f32e5c11 completed June 20, 2026, 10:45 p.m.
NEDg Description generation batch_6a3718ac3e888190ae09adc2f6507e91 completed June 20, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a37192386e08190a954074052306e82 completed June 20, 2026, 10:50 p.m.
Created at: May 1, 2026, 1:59 a.m.