Triple

T14325595
Position Surface form Disambiguated ID Type / Status
Subject Angers – Loire Airport E355206 entity
Predicate IATAcode P418 FINISHED
Object ANE
ANE is the IATA airport code for Angers – Loire Airport, a regional airport serving the Angers area in western France.
 E1093392 NE FINISHED

How this triple was built (4 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: [Angers – Loire Airport, IATAcode, ANE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANE
Context triple: [Angers – Loire Airport, IATAcode, ANE]
  • A. ANE
    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. ANO
    ANO is the ICAO airline designator assigned to Airnorth, a regional airline based in Australia.
  • 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 commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ANE
Triple: [Angers – Loire Airport, IATAcode, ANE]
Generated description
ANE is the IATA airport code for Angers – Loire Airport, a regional airport serving the Angers area in western France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANE
Target entity description: ANE is the IATA airport code for Angers – Loire Airport, a regional airport serving the Angers area in western France.
  • A. ANE
    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. ANO
    ANO is the ICAO airline designator assigned to Airnorth, a regional airline based in Australia.
  • 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 commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • F. None of above. chosen

Provenance (5 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de883e6a288190b6c22f630a1eef3c completed April 14, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4690a79c819099cc4ae9a10ba0db completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd47bbc5e081908aa8b0e76661234f completed May 8, 2026, 2:17 a.m.
NED2 Entity disambiguation (via description) batch_69fd4840f0688190975d8c3c7eefb132 completed May 8, 2026, 2:19 a.m.
Created at: April 10, 2026, 1:13 a.m.