Triple

T15024457
Position Surface form Disambiguated ID Type / Status
Subject General Francisco Javier Mina International Airport E378172 entity
Predicate IATAcode P418 FINISHED
Object TAM E759594 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: TAM | Statement: [General Francisco Javier Mina International Airport, IATAcode, TAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAM
Context triple: [General Francisco Javier Mina International Airport, IATAcode, TAM]
  • A. TAM
    TAM is the standard abbreviation used for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
  • B. TAM chosen
    TAM is the former brand name and airline code of LATAM Airlines Brasil, one of Brazil’s largest commercial airlines.
  • C. TAM
    TAM is a Georgian aerospace company based in Tbilisi that designs, manufactures, and services aircraft and related aviation components.
  • D. TAM
    TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
  • E. TAMSE
    TAMSE is an Argentine state-owned defense manufacturer best known for producing the TAM family of medium tanks and other armored vehicles.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7de117c8190a1b9fa8d1602057e completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dd499108190b803c6afc0fa00bc completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 2:56 a.m.