Triple

T1310582
Position Surface form Disambiguated ID Type / Status
Subject Orlando International Airport E27980 entity
Predicate IATAcode P418 FINISHED
Object MCO
MCO is the IATA airport code for Orlando International Airport, a major air travel hub serving the Orlando, Florida metropolitan area and its tourist attractions.
E148977 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: MCO | Statement: [Orlando International Airport, IATAcode, MCO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MCO
Context triple: [Orlando International Airport, IATAcode, MCO]
  • A. MCO
    MCO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Principality of Monaco.
  • B. MCO
    MCO is the National Rail station code used to identify Oxford Road railway station in Manchester, England.
  • C. MCRC
    MCRC is the United States Marine Corps Recruiting Command responsible for enlisting and accessing new Marines into the Corps.
  • D. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • E. NMOC
    NMOC is an abbreviation commonly used for a Network Manager Operations Centre, a facility responsible for overseeing and coordinating network operations and performance.
  • 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: MCO
Triple: [Orlando International Airport, IATAcode, MCO]
Generated description
MCO is the IATA airport code for Orlando International Airport, a major air travel hub serving the Orlando, Florida metropolitan area and its tourist attractions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MCO
Target entity description: MCO is the IATA airport code for Orlando International Airport, a major air travel hub serving the Orlando, Florida metropolitan area and its tourist attractions.
  • A. MCO
    MCO is the National Rail station code used to identify Oxford Road railway station in Manchester, England.
  • B. MCO
    MCO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Principality of Monaco.
  • C. MCRC
    MCRC is the United States Marine Corps Recruiting Command responsible for enlisting and accessing new Marines into the Corps.
  • D. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • E. NMOC
    NMOC is an abbreviation commonly used for a Network Manager Operations Centre, a facility responsible for overseeing and coordinating network operations and performance.
  • 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c15490a88190872c3d2698a8f9c9 completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb30b45708190aaf8c977fef2500c completed March 7, 2026, 11:21 p.m.
NEDg Description generation batch_69acb389ab248190b67eb802ed1ac01f completed March 7, 2026, 11:23 p.m.
NED2 Entity disambiguation (via description) batch_69acb423e2948190b3927d2f041b6215 completed March 7, 2026, 11:26 p.m.
Created at: March 1, 2026, 7:51 p.m.