Triple

T12872040
Position Surface form Disambiguated ID Type / Status
Subject Zagora E307873 entity
Predicate transport P230 FINISHED
Object Zagora Airport E307874 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: Zagora Airport | Statement: [Zagora, transport, Zagora Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagora Airport
Context triple: [Zagora, transport, Zagora Airport]
  • A. Zagora Airport chosen
    Zagora Airport is a small regional airport in southeastern Morocco that serves as a gateway for travelers heading into the nearby Sahara Desert and surrounding desert attractions.
  • B. Almería Airport
    Almería Airport is a regional international airport in southeastern Spain that serves the city of Almería and the surrounding Costa de Almería tourist area.
  • C. Ghadames Airport
    Ghadames Airport is a regional airport in western Libya that serves the historic oasis town of Ghadames and connects it to the country’s broader air transport network.
  • D. Araxos Airport
    Araxos Airport is a regional and military airport serving the area of Patras in western Greece.
  • E. Melilla Airport
    Melilla Airport is a small regional airport in the Spanish autonomous city of Melilla on the north coast of Africa, providing domestic connections to mainland Spain.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970905784819091631161a9de98c5 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bb4b28c8190a4ec9cad4e1e0f05 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:38 p.m.