Triple

T1458412
Position Surface form Disambiguated ID Type / Status
Subject Aerolíneas Argentinas E31451 entity
Predicate IATACode P418 FINISHED
Object AR
AR is the two-letter IATA airline designator assigned to Aerolíneas Argentinas, the flag carrier of Argentina.
 E168125 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: AR | Statement: [Aerolíneas Argentinas, IATACode, AR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AR
Context triple: [Aerolíneas Argentinas, IATACode, AR]
  • A. AR
    AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
  • B. AR
    AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
  • C. ARS
    ARS is the principal in-house research agency of the United States Department of Agriculture, conducting scientific studies to improve agriculture, food safety, and environmental quality.
  • D. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • E. RA
    RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
  • 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: AR
Triple: [Aerolíneas Argentinas, IATACode, AR]
Generated description
AR is the two-letter IATA airline designator assigned to Aerolíneas Argentinas, the flag carrier of Argentina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AR
Target entity description: AR is the two-letter IATA airline designator assigned to Aerolíneas Argentinas, the flag carrier of Argentina.
  • A. AR
    AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
  • B. AR
    AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
  • C. ARS
    ARS is the principal in-house research agency of the United States Department of Agriculture, conducting scientific studies to improve agriculture, food safety, and environmental quality.
  • D. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • E. RA
    RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c59a462881908e84b27846a6bc04 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e7643e081909a088035faf2022d completed March 8, 2026, 5:51 a.m.
NEDg Description generation batch_69ad121fee9c81909efddee10191b791 completed March 8, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69ad127f25548190bdbcf99132237ad4 completed March 8, 2026, 6:09 a.m.
Created at: March 1, 2026, 8 p.m.