Triple

T9193012
Position Surface form Disambiguated ID Type / Status
Subject Gardabya Airport E220634 entity
Predicate locatedIn P40 FINISHED
Object Sirte E42055 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: Sirte | Statement: [Gardabya Airport, locatedIn, Sirte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sirte
Context triple: [Gardabya Airport, locatedIn, Sirte]
  • A. Sirte, Libya chosen
    Sirte, Libya is a coastal city on the Mediterranean Sea that gained international prominence as Muammar Gaddafi’s final stronghold and the site of his death during the 2011 Libyan civil war.
  • B. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • C. Tripoli
    Tripoli is Lebanon’s second-largest city, a historic Mediterranean port known for its medieval Mamluk architecture and vibrant commercial life.
  • D. Tripoli
    Tripoli is a historic city in the central Peloponnese of Greece that serves as the main urban and administrative center of the Arcadia region.
  • E. Zintan
    Zintan is a town in western Libya known for its role in the Libyan Civil War and for being controlled by powerful local militias.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5c1fa9c8190bc5cc6dce8778694 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09b8b37488190b72f2b4c55fd9a8c completed April 4, 2026, 5:03 a.m.
Created at: March 30, 2026, 7:24 p.m.