Triple

T18456652
Position Surface form Disambiguated ID Type / Status
Subject SS26 E450918 entity
Predicate maintainedBy P86 FINISHED
Object ANAS 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: ANAS | Statement: [SS26, maintainedBy, ANAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANAS
Context triple: [SS26, maintainedBy, ANAS]
  • A. ANAS
    ANAS is the primary state research institution in Azerbaijan, overseeing and coordinating scientific activities and academic research across the country.
  • B. ANAS chosen
    ANAS is Italy’s national road agency responsible for the construction, maintenance, and management of much of the country’s road and motorway network.
  • C. Anka-S
    Anka-S is a Turkish-made, satellite-controlled, medium-altitude long-endurance (MALE) unmanned aerial vehicle designed for extended surveillance and reconnaissance missions.
  • D. Ansen
    Ansen is a small village in the Dutch province of Drenthe, located within the municipality of De Wolden.
  • E. ANE
    ANE is the IATA airport code for Angers – Loire Airport, a regional airport serving the Angers area in western France.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264ce5948190b57baa2ea71297a9 completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.