Triple

T6706471
Position Surface form Disambiguated ID Type / Status
Subject Runway 17R/35L E153017 entity
Predicate belongsToAirportWithIATA P45234 FINISHED
Object MCO E148977 NE FINISHED

How this triple was built (3 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: [Runway 17R/35L, belongsToAirportWithIATA, MCO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MCO
Context triple: [Runway 17R/35L, belongsToAirportWithIATA, MCO]
  • 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. MCO chosen
    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.
  • D. MCO
    MCO is the stock ticker symbol for Moody's Corporation, a leading global provider of credit ratings, research, and risk analysis.
  • E. MCoE
    MCoE is the U.S. Army’s primary training and doctrine center for maneuver forces, integrating infantry, armor, and related capabilities at Fort Moore, Georgia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: belongsToAirportWithIATA
Context triple: [Runway 17R/35L, belongsToAirportWithIATA, MCO]
  • A. belongsToAirport
    Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
  • B. belongsToAirportSystem
    Indicates that an airport is a member or component of a specific airport system or network.
  • C. associatedWithAirportName
    Indicates a relationship where an entity is linked or connected to a specific airport by its name.
  • D. associatedWithAirportCode chosen
    Indicates that one entity has a relationship or connection to an airport identified by a specific airport code.
  • E. associatedAirport
    Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
  • F. None of above.

Provenance (4 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d16897e48190b43eda2206b14d6a completed March 27, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f7df860819099d50871dbe08ad9 completed March 28, 2026, 1:31 a.m.
PD Predicate disambiguation batch_69c6d089c7488190a00853fb12f53b2a completed March 27, 2026, 6:46 p.m.
Created at: March 27, 2026, 2:06 p.m.