Triple

T17865158
Position Surface form Disambiguated ID Type / Status
Subject SuperCinecolor E446678 entity
Predicate competesWith P1375 FINISHED
Object Eastmancolor NE NERFINISHED

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: Eastmancolor | Statement: [SuperCinecolor, competesWith, Eastmancolor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eastmancolor
Context triple: [SuperCinecolor, competesWith, Eastmancolor]
  • A. Eastmancolor chosen
    Eastmancolor is a color motion picture film process developed by Eastman Kodak that became widely used in the mid-20th century as a more economical alternative to earlier color systems like Technicolor.
  • B. Ricoh
    Ricoh is a Japanese multinational imaging and electronics company best known for its cameras, printers, copiers, and office equipment solutions.
  • C. Konica Minolta
    Konica Minolta is a Japanese multinational technology company best known for its imaging products, including printers, copiers, and optical devices.
  • D. Ansco Color
    Ansco Color was a mid-20th-century color motion picture film process and stock developed by the Ansco company as an alternative to more dominant systems like Technicolor and Eastmancolor.
  • E. FUJ
    FUJ is the vehicle registration code used on license plates issued in the Emirate of Fujairah in the United Arab Emirates.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49793a2588190bb341ac606d767fe completed April 19, 2026, 8:51 a.m.
Created at: April 10, 2026, 10:17 a.m.