Triple

T22345977
Position Surface form Disambiguated ID Type / Status
Subject Comet Line E552391 entity
Predicate typicalDestinationCity P35234 FINISHED
Object San Sebastián NE NERFINISHED

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: San Sebastián | Statement: [Comet Line, typicalDestinationCity, San Sebastián]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Sebastián
Context triple: [Comet Line, typicalDestinationCity, San Sebastián]
  • A. San Sebastián
    San Sebastián is a small town located within the Comayagua Department of central Honduras.
  • B. San Sebastián
    San Sebastián is a district and urban area within the San José metropolitan region of Costa Rica, known for its residential neighborhoods and proximity to the country’s capital.
  • C. San Sebastián
    San Sebastián is a Guatemalan town located in the highlands of the San Marcos department, known for its proximity to Central America’s highest peak, Volcán Tajumulco.
  • D. Donostia-San Sebastián chosen
    Donostia-San Sebastián is a coastal city in Spain’s Basque Country renowned for its picturesque bay, beaches, and world-class gastronomy.
  • E. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • 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: typicalDestinationCity
Context triple: [Comet Line, typicalDestinationCity, San Sebastián]
  • A. typicalDestinationMetroArea
    Indicates the metro area that is most commonly the destination associated with a given origin or context.
  • B. destinationCity chosen
    Indicates the city to which an entity is traveling, being sent, or ultimately directed.
  • C. typicalVenueCity
    Indicates that a particular city is the usual or standard location where an event, activity, or organization is typically held or based.
  • D. typicalDestinationAirportIATA
    Indicates the IATA airport code that is typically the destination in this kind of trip or route.
  • E. typicalStopoverCity
    Indicates that a city commonly serves as an intermediate stop or layover point in a journey between other locations.
  • F. None of above.

Provenance (3 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_69e11e494eec81909c4d2d51f69499d9 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157981c0881909ac74d68b99075c2 completed April 29, 2026, 12:58 a.m.
PD Predicate disambiguation batch_69e7300c20088190a59e5bf9e70384f3 completed April 21, 2026, 8:06 a.m.
Created at: April 16, 2026, 8:43 p.m.