Triple

T3034311
Position Surface form Disambiguated ID Type / Status
Subject ANA Aeroportos de Portugal E82970 entity
Predicate abbreviation P43 FINISHED
Object ANA
ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
 E321521 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: ANA | Statement: [ANA Aeroportos de Portugal, abbreviation, ANA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANA
Context triple: [ANA Aeroportos de Portugal, abbreviation, ANA]
  • A. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • B. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • C. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • D. ANE
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • E. AN
    AN is the vehicle registration code used on license plates for the Ansbach district in the Middle Franconia region of Bavaria, Germany.
  • 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: ANA
Triple: [ANA Aeroportos de Portugal, abbreviation, ANA]
Generated description
ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANA
Target entity description: ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • A. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • B. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • C. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • D. ANE
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • E. AN
    AN is the vehicle registration code used on license plates for the Ansbach district in the Middle Franconia region of Bavaria, Germany.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b2a40b48190bfa7cdbb0fbd87f8 completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1dec30d8081909d6ee691e5e51434 completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1e297ddc0819092942cdf8a4f9440 completed March 11, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_69b1e2f519108190883ee481b763b67f completed March 11, 2026, 9:47 p.m.
Created at: March 8, 2026, 3:01 p.m.