Triple

T16967019
Position Surface form Disambiguated ID Type / Status
Subject Strada Statale 640 E411566 entity
Predicate maintainedBy P86 FINISHED
Object ANAS E535717 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: ANAS | Statement: [Strada Statale 640, maintainedBy, ANAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANAS
Context triple: [Strada Statale 640, 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 Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0a548b48190b87468630f3e3209 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d46f1d608190befe4dcbda086c03 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.