Triple

T36132525
Position Surface form Disambiguated ID Type / Status
Subject The Dragon Painter E1045060 entity
Predicate distributor P1951 FINISHED
Object Robertson-Cole Distributing Corporation
Robertson-Cole Distributing Corporation was an early 20th-century American film distribution company active during the silent film era.
E2169456 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: Robertson-Cole Distributing Corporation | Statement: [The Dragon Painter, distributor, Robertson-Cole Distributing Corporation]
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: Robertson-Cole Distributing Corporation
Triple: [The Dragon Painter, distributor, Robertson-Cole Distributing Corporation]
Generated description
Robertson-Cole Distributing Corporation was an early 20th-century American film distribution company active during the silent film era.

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_69f76e36a4508190b5bfc8f594272a4c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b33448dc81909de8f20f2dc44d75 completed May 3, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38de1767908190a8187a2d31e65422 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38f40acb308190aff77733b25dfaed completed June 22, 2026, 8:36 a.m.
NED2 Entity disambiguation (via description) batch_6a38f7c56b90819082c99f6e90f235e7 completed June 22, 2026, 8:52 a.m.
Created at: May 3, 2026, 4:08 p.m.