Triple

T1226435
Position Surface form Disambiguated ID Type / Status
Subject Adolfo Suárez Madrid–Barajas Airport E26337 entity
Predicate IATAcode P418 FINISHED
Object MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
 E140782 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: MAD | Statement: [Adolfo Suárez Madrid–Barajas Airport, IATAcode, MAD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAD
Context triple: [Adolfo Suárez Madrid–Barajas Airport, IATAcode, MAD]
  • A. MDA
    MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
  • B. MDA
    MDA is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of Moldova.
  • C. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. MIA
    MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
  • 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: MAD
Triple: [Adolfo Suárez Madrid–Barajas Airport, IATAcode, MAD]
Generated description
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAD
Target entity description: MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
  • A. MDA
    MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
  • B. MDA
    MDA is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of Moldova.
  • C. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. MIA
    MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be39908481908cca21aaf0828415 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a0fcf508190be3668bd55f6f6d6 completed March 7, 2026, 8:26 p.m.
NEDg Description generation batch_69ac8ab214c48190a60c6604a67f9cf2 completed March 7, 2026, 8:29 p.m.
NED2 Entity disambiguation (via description) batch_69ac8b0db83c81909db3c501a435f1d1 completed March 7, 2026, 8:31 p.m.
Created at: March 1, 2026, 7:47 p.m.