Triple

T11978286
Position Surface form Disambiguated ID Type / Status
Subject LTBJ E285090 entity
Predicate operator P179 FINISHED
Object TAV Airports E285091 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: TAV Airports | Statement: [LTBJ, operator, TAV Airports]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAV Airports
Context triple: [LTBJ, operator, TAV Airports]
  • A. TAV Airports Holding chosen
    TAV Airports Holding is a Turkish airport operating company that manages and develops a network of airports primarily in Turkey and other countries.
  • B. Hermes Airports Ltd
    Hermes Airports Ltd is a Cypriot airport management company responsible for operating and developing major international airports in Cyprus.
  • C. NMIA Airports Limited
    NMIA Airports Limited is the company responsible for managing and operating Jamaica’s Norman Manley International Airport in Kingston.
  • D. Vinci Airports
    Vinci Airports is a global airport operator that manages and develops a large network of airports across multiple countries as part of the Vinci Group’s transport infrastructure portfolio.
  • E. VINCI Airports
    VINCI Airports is a major global airport operator that manages and develops a large network of airports across multiple countries.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471f6afc48190856a0f7c486b28aa completed May 1, 2026, 9:27 a.m.
Created at: April 8, 2026, 9:46 p.m.