Triple

T15547793
Position Surface form Disambiguated ID Type / Status
Subject Aguascalientes International Airport E370657 entity
Predicate hasICAOcode P419 FINISHED
Object MMAS
MMAS is the ICAO airport code for Aguascalientes International Airport in Aguascalientes, Mexico.
 E1163831 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: MMAS | Statement: [Aguascalientes International Airport, hasICAOcode, MMAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MMAS
Context triple: [Aguascalientes International Airport, hasICAOcode, MMAS]
  • A. MASI
    MASI is the main all-share stock market index of the Casablanca Stock Exchange in Morocco, tracking the performance of its listed companies.
  • B. MMSM
    MMSM is the ICAO airport code assigned to Felipe Ángeles International Airport, a major commercial airport serving the Mexico City metropolitan area.
  • C. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • D. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • E. MAS
    MAS is the official Indian Railways station code for Chennai Central, one of the busiest and most important railway terminals in South India.
  • 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: MMAS
Triple: [Aguascalientes International Airport, hasICAOcode, MMAS]
Generated description
MMAS is the ICAO airport code for Aguascalientes International Airport in Aguascalientes, Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MMAS
Target entity description: MMAS is the ICAO airport code for Aguascalientes International Airport in Aguascalientes, Mexico.
  • A. MASI
    MASI is the main all-share stock market index of the Casablanca Stock Exchange in Morocco, tracking the performance of its listed companies.
  • B. MMSM
    MMSM is the ICAO airport code assigned to Felipe Ángeles International Airport, a major commercial airport serving the Mexico City metropolitan area.
  • C. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • D. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • E. MAS
    MAS is a sports club based in Saint-Étienne, France, known for its participation in regional football competitions.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9073948190b6e9cf504aacc7cf completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455c172c8190833274cb98667e84 completed May 9, 2026, 2:31 p.m.
NEDg Description generation batch_69ff469e47fc819099d08f780ad81bf5 completed May 9, 2026, 2:37 p.m.
NED2 Entity disambiguation (via description) batch_69ff47aeddac8190a87024019ecb1396 completed May 9, 2026, 2:41 p.m.
Created at: April 10, 2026, 4:08 a.m.