Triple

T4691727
Position Surface form Disambiguated ID Type / Status
Subject Tram 28 route E104048 entity
Predicate passesThrough P225 FINISHED
Object Graça E108959 NE FINISHED

How this triple was built (2 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: Graça | Statement: [Tram 28 route, passesThrough, Graça]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graça
Context triple: [Tram 28 route, passesThrough, Graça]
  • A. Graça chosen
    Graça is a historic hilltop neighborhood in Lisbon, Portugal, known for its traditional streets, viewpoints over the city, and classic tram connections.
  • B. Chiado
    Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
  • C. Campoalegre
    Campoalegre is a municipality and town in southwestern Colombia, located in the Huila Department and known for its agricultural production.
  • D. San-São
    San-São is the traditional Brazilian football derby between São Paulo FC and Santos FC, known for its historic rivalries and memorable matches.
  • E. Vitória
    Vitória is the capital city of the Brazilian state of Espírito Santo, known for its coastal setting, port activities, and surrounding islands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd639c94608190808e535d0abd08a0 completed March 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03bd47b08190a3d2a174eb2f7b2e completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:16 p.m.