Triple

T8414967
Position Surface form Disambiguated ID Type / Status
Subject Apple Neural Engine E198710 entity
Predicate abbreviation P43 FINISHED
Object ANE E198710 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: ANE | Statement: [Apple Neural Engine, abbreviation, ANE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANE
Context triple: [Apple Neural Engine, abbreviation, ANE]
  • A. ANE chosen
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • B. ANE
    ANE is the ICAO airline designator assigned to Iberia Regional, the regional airline brand operated by Air Nostrum in Spain.
  • C. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • D. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • E. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e443a08190983d9a0a61e0f781 completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce032a25ec819094c6346eb2a7f973 completed April 2, 2026, 5:48 a.m.
Created at: March 30, 2026, 6:06 p.m.