Triple

T21996045
Position Surface form Disambiguated ID Type / Status
Subject Fernando de Noronha Airport E543208 entity
Predicate IATAcode P418 FINISHED
Object FEN 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: FEN | Statement: [Fernando de Noronha Airport, IATAcode, FEN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FEN
Context triple: [Fernando de Noronha Airport, IATAcode, FEN]
  • A. FEN chosen
    FEN is the IATA airport code for the main airport serving Brazil’s Fernando de Noronha Archipelago, a remote Atlantic island destination.
  • B. Figuerismo
    Figuerismo is a Costa Rican political ideology inspired by the leadership and reforms of José Figueres Ferrer, emphasizing social democracy, demilitarization, and strong public institutions.
  • C. Fiez
    Fiez is a small municipality in the canton of Vaud in western Switzerland, situated in the Jura-Nord vaudois district.
  • D. FICS
    FICS is the Firearms Instant Check System operated by the Oregon State Police to conduct background checks on firearm purchasers.
  • E. FICS
    FICS is the main secondary school in the Falkland Islands, providing education to local students in the capital, Stanley.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276493bc81908567445e901bc3a7 completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:19 p.m.