Triple

T26610231
Position Surface form Disambiguated ID Type / Status
Subject Allan F. Nicholls E667894 entity
Predicate notableWork P4 FINISHED
Object Vincent & Theo
Vincent & Theo is a 1990 biographical drama film directed by Robert Altman that explores the turbulent lives and relationship of painter Vincent van Gogh and his brother Theo.
E1731064 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: Vincent & Theo | Statement: [Allan F. Nicholls, notableWork, Vincent & Theo]
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: Vincent & Theo
Triple: [Allan F. Nicholls, notableWork, Vincent & Theo]
Generated description
Vincent & Theo is a 1990 biographical drama film directed by Robert Altman that explores the turbulent lives and relationship of painter Vincent van Gogh and his brother Theo.

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_69ee9cfd20348190bb1255d2603efb7a completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615a87a5881908a96dcc673adc3b5 completed May 2, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c8479aa48190bde51181cb2a9fa1 completed May 23, 2026, 3:31 p.m.
NEDg Description generation batch_6a11c8f290bc8190bfa1990ee7119516 completed May 23, 2026, 3:34 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca7256dc81908499e290c0b32b39 completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 2:16 a.m.