Triple

T15411195
Position Surface form Disambiguated ID Type / Status
Subject Los Mochis International Airport E368595 entity
Predicate ICAOcode P419 FINISHED
Object MMLM
MMLM is the ICAO airport code for Los Mochis International Airport in Sinaloa, Mexico.
E1156066 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: MMLM | Statement: [Los Mochis International Airport, ICAOcode, MMLM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MMLM
Context triple: [Los Mochis International Airport, ICAOcode, MMLM]
  • A. MML
    MML is a major inter-city rail route in England connecting London with key cities in the East Midlands and South Yorkshire.
  • B. MMML
    MMML is the ICAO airport code for Mexicali International Airport in Mexicali, Baja California, Mexico.
  • C. MMLP
    MMLP is the ICAO airport code for Manuel Márquez de León International Airport serving La Paz, Baja California Sur, Mexico.
  • D. MMLO
    MMLO is the ICAO airport code for Guanajuato International Airport, a major air transport hub serving the León–Guanajuato region in central Mexico.
  • E. MLU
    MLU is the IATA airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
  • 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: MMLM
Triple: [Los Mochis International Airport, ICAOcode, MMLM]
Generated description
MMLM is the ICAO airport code for Los Mochis International Airport in Sinaloa, Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MMLM
Target entity description: MMLM is the ICAO airport code for Los Mochis International Airport in Sinaloa, Mexico.
  • A. MML
    MML is a major inter-city rail route in England connecting London with key cities in the East Midlands and South Yorkshire.
  • B. MMML
    MMML is the ICAO airport code for Mexicali International Airport in Mexicali, Baja California, Mexico.
  • C. MMLP
    MMLP is the ICAO airport code for Manuel Márquez de León International Airport serving La Paz, Baja California Sur, Mexico.
  • D. MMLO
    MMLO is the ICAO airport code for Guanajuato International Airport, a major air transport hub serving the León–Guanajuato region in central Mexico.
  • E. MLU
    MLU is the IATA airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea600b48190a3dbca1a68a2a1cd completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a7356548190af5651ab0bc03ab9 completed May 9, 2026, 11:28 a.m.
NEDg Description generation batch_69ff1afa99888190bfb60fd88d840d4e completed May 9, 2026, 11:31 a.m.
NED2 Entity disambiguation (via description) batch_69ff1bdb39b481908f0b1df595837bc4 completed May 9, 2026, 11:34 a.m.
Created at: April 10, 2026, 3:20 a.m.