Triple

T9065716
Position Surface form Disambiguated ID Type / Status
Subject AANES E217240 entity
Predicate shortName P43 FINISHED
Object AANES E217240 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: AANES | Statement: [AANES, shortName, AANES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AANES
Context triple: [AANES, shortName, AANES]
  • A. AANES chosen
    AANES is a de facto self-governing political entity in northern and eastern Syria, often associated with Kurdish-led, multi-ethnic autonomous administration and its experiment in decentralized, democratic governance.
  • B. ANE
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • C. ANE
    ANE is the ICAO airline designator assigned to Iberia Regional, the regional airline brand operated by Air Nostrum in Spain.
  • D. ANLE
    ANLE is the North American Academy of the Spanish Language, an institution dedicated to studying, preserving, and promoting the correct use of Spanish in the United States.
  • E. ANEP
    ANEP is Uruguay’s National Administration of Public Education, the autonomous body responsible for overseeing and managing the country’s public education system.
  • 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_69ca83d5a7f48190b16c1e59bd43ede0 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc94bc91d48190acf62afa90eec079 completed April 1, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffdd4ad78819098f64d8440c7fa96 completed April 3, 2026, 5:50 p.m.
Created at: March 30, 2026, 7:11 p.m.