Triple

T8824244
Position Surface form Disambiguated ID Type / Status
Subject Chemische Fabrik Griesheim-Elektron E209974 entity
Predicate sharesMergedWith P84826 FINISHED
Object Agfa E209972 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: Agfa | Statement: [Chemische Fabrik Griesheim-Elektron, sharesMergedWith, Agfa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agfa
Context triple: [Chemische Fabrik Griesheim-Elektron, sharesMergedWith, Agfa]
  • A. Agfa chosen
    Agfa is a historic German company best known for its photographic films, cameras, and imaging technologies.
  • B. Gauda
    Gauda was a historic region in eastern India, centered in present-day West Bengal and Bangladesh, that served as an important political and cultural center in early medieval times.
  • C. Galafi
    Galafi is a small border town in Djibouti that serves as a key road crossing and trade gateway between Djibouti and Ethiopia.
  • D. Afa
    Afa is a small commune in the Corse-du-Sud department on the French island of Corsica, located inland near the Gulf of Ajaccio.
  • E. Fager
    Fager is a surname most notably associated with American television producer and former CBS News chairman Jeff Fager.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8365b28081909e48e45e95dfc405 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc603220508190b64e22dec3ee5ceb completed April 1, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_69cf893e08b0819083c2d152d0f9c263 completed April 3, 2026, 9:32 a.m.
Created at: March 30, 2026, 6:46 p.m.