Triple

T6545635
Position Surface form Disambiguated ID Type / Status
Subject Antonio Maceo International Airport E150999 entity
Predicate ICAOcode P419 FINISHED
Object MUCU
MUCU is the ICAO airport code for Antonio Maceo International Airport in Santiago de Cuba, Cuba.
 E604413 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: MUCU | Statement: [Antonio Maceo International Airport, ICAOcode, MUCU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MUCU
Context triple: [Antonio Maceo International Airport, ICAOcode, MUCU]
  • A. MUC
    MUC is the IATA airport code for Munich Airport, a major international aviation hub in Germany.
  • B. MUC
    MUC is the abbreviation for the Meritorious Unit Commendation, a U.S. military unit award recognizing exceptionally meritorious conduct in the performance of outstanding services.
  • C. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • D. Muhu
    Muhu is a large Estonian island in the Baltic Sea known for its traditional villages, distinctive folk culture, and role as a gateway between the mainland and Saaremaa.
  • E. MAU
    MAU (Media Access Unit) is a network device used in IEEE 802.5 Token Ring networks to connect multiple stations and manage the ring’s physical topology.
  • 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: MUCU
Triple: [Antonio Maceo International Airport, ICAOcode, MUCU]
Generated description
MUCU is the ICAO airport code for Antonio Maceo International Airport in Santiago de Cuba, Cuba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MUCU
Target entity description: MUCU is the ICAO airport code for Antonio Maceo International Airport in Santiago de Cuba, Cuba.
  • A. MUC
    MUC is the abbreviation for the Meritorious Unit Commendation, a U.S. military unit award recognizing exceptionally meritorious conduct in the performance of outstanding services.
  • B. MUC
    MUC is the IATA airport code for Munich Airport, a major international aviation hub in Germany.
  • C. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • D. Muhu
    Muhu is a large Estonian island in the Baltic Sea known for its traditional villages, distinctive folk culture, and role as a gateway between the mainland and Saaremaa.
  • E. MAU
    MAU (Media Access Unit) is a network device used in IEEE 802.5 Token Ring networks to connect multiple stations and manage the ring’s physical topology.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adee47cc8190830dbc1228b788ee completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d54814848190bc397d9b81abc042 completed March 27, 2026, 7:06 p.m.
NEDg Description generation batch_69c6d67574cc8190acf20c1a598c32ee completed March 27, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69c6d83b53e48190881a3e1e8fa8b168 completed March 27, 2026, 7:19 p.m.
Created at: March 27, 2026, 1:50 p.m.