Triple

T10959785
Position Surface form Disambiguated ID Type / Status
Subject Arabica E258939 entity
Predicate commonName P570 FINISHED
Object Arabica coffee E258939 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: Arabica coffee | Statement: [Arabica, commonName, Arabica coffee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arabica coffee
Context triple: [Arabica, commonName, Arabica coffee]
  • A. Arabica chosen
    Arabica is a high-quality coffee species prized for its smooth, aromatic flavor and widely used in premium coffee varieties worldwide.
  • B. Sidamo
    Sidamo is a Cushitic language spoken primarily in southern Ethiopia by the Sidama people.
  • C. Blue Mountains coffee
    Blue Mountains coffee is a highly prized Jamaican coffee variety renowned for its mild flavor, smooth body, and low bitterness, grown at high elevations in the Blue Mountains region.
  • D. Caffa
    Caffa is the historical name of the Crimean port city now known as Feodosia, which was a major Genoese trading colony and a key Black Sea commercial hub in the Middle Ages.
  • E. Coffee
    "Coffee" is a song by the American singer-songwriter Miguel, known for its smooth blend of R&B and sensual, atmospheric production.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77127b10481908ad1efafb2a338d1 completed April 9, 2026, 9:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d751e8e081908f31ab2d82105c3c completed April 18, 2026, 12:58 a.m.
Created at: April 8, 2026, 9:23 p.m.