Triple

T2689020
Position Surface form Disambiguated ID Type / Status
Subject Del Norte International Airport E57553 entity
Predicate ICAO code P419 FINISHED
Object MMAN
MMAN is the ICAO airport code for Del Norte International Airport in Monterrey, Mexico.
 E287671 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: MMAN | Statement: [Del Norte International Airport, ICAO code, MMAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MMAN
Context triple: [Del Norte International Airport, ICAO code, MMAN]
  • A. MM
    MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
  • B. NNMC
    NNMC is the commonly used abbreviation for the National Naval Medical Center, the former U.S. Navy flagship hospital in Bethesda, Maryland.
  • C. MMFA
    MMFA is the acronym for the Montgomery Museum of Fine Arts, a prominent art museum in Montgomery, Alabama known for its collections of American art and regional works.
  • D. MAM
    MAM is a prominent modern art museum in Mexico City known for its extensive collection of 20th- and 21st-century Mexican and international artworks.
  • E. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • 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: MMAN
Triple: [Del Norte International Airport, ICAO code, MMAN]
Generated description
MMAN is the ICAO airport code for Del Norte International Airport in Monterrey, Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MMAN
Target entity description: MMAN is the ICAO airport code for Del Norte International Airport in Monterrey, Mexico.
  • A. MM
    MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
  • B. NNMC
    NNMC is the commonly used abbreviation for the National Naval Medical Center, the former U.S. Navy flagship hospital in Bethesda, Maryland.
  • C. MMFA
    MMFA is the acronym for the Montgomery Museum of Fine Arts, a prominent art museum in Montgomery, Alabama known for its collections of American art and regional works.
  • D. MAM
    MAM is a prominent modern art museum in Mexico City known for its extensive collection of 20th- and 21st-century Mexican and international artworks.
  • E. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9f380d48190953529d23688a328 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa0741bc48190adffe6cfae831e26 completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa13a81bc819091463e6589e72361 completed March 10, 2026, 4:42 a.m.
NED2 Entity disambiguation (via description) batch_69afa1ab8da8819090af3ed60b417040 completed March 10, 2026, 4:44 a.m.
Created at: March 6, 2026, 9:54 p.m.