Triple

T6508733
Position Surface form Disambiguated ID Type / Status
Subject Expo 93 E150074 entity
Predicate nextExpoCity P58162 FINISHED
Object Lisbon E3151 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: Lisbon | Statement: [Expo 93, nextExpoCity, Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon
Context triple: [Expo 93, nextExpoCity, Lisbon]
  • A. Lisbon chosen
    Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
  • B. Lisbon
    Lisbon is the alias of Raquel Murillo, a former police inspector who becomes one of the central members of the Professor’s gang in the Spanish series "Money Heist" (La Casa de Papel).
  • C. Porto
    Porto is Portugal’s second-largest city, renowned for its historic riverside district, rich maritime heritage, and production of port wine.
  • D. Porto
    Porto is a small coastal town in western Corsica, France, known as the main gateway to the scenic Gulf of Porto and its surrounding natural reserves and rock formations.
  • E. Coimbra
    Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
  • 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: nextExpoCity
Context triple: [Expo 93, nextExpoCity, Lisbon]
  • A. nextExpoHostCity chosen
    Indicates that one city is designated to host the next scheduled Expo event relative to another city or time reference.
  • B. previousExpo
    Indicates that one entity is an exposition or expo event that occurred immediately before another in a temporal or sequential order.
  • C. nextEdition
    Indicates that one entity is the immediate subsequent edition or version that follows another in a sequence.
  • D. nextShuttleFlightAfterDisaster
    Indicates the first shuttle flight that took place after a specified disaster event.
  • E. previousAttraction
    Indicates that one entity was formerly an attraction or point of interest associated with another entity in the past.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f386aa08190bfc8592a92ec6339 completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb0ff914819080b1721ccbc56571 completed March 27, 2026, 6:23 p.m.
PD Predicate disambiguation batch_69c68ab714908190aa7c2fbf64078e15 completed March 27, 2026, 1:48 p.m.
Created at: March 27, 2026, 1:43 p.m.