Triple

T504371
Position Surface form Disambiguated ID Type / Status
Subject Comboios de Portugal E10469 entity
Predicate brand P1500 FINISHED
Object Intercidades E20070 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: Intercidades | Statement: [Comboios de Portugal, brand, Intercidades]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Intercidades
Context triple: [Comboios de Portugal, brand, Intercidades]
  • A. Tren Urbano
    Tren Urbano is a rapid transit rail system serving the San Juan metropolitan area in Puerto Rico, providing urban mass transportation across key municipalities.
  • B. São Paulo Metro
    The São Paulo Metro is a major rapid transit system serving the city of São Paulo, Brazil, known for its extensive network, high ridership, and role as a backbone of the city's public transportation.
  • C. InterCity chosen
    InterCity is a category of long-distance passenger trains in several European countries, notably providing fast, regular intercity rail services.
  • D. Tren Ligero
    Tren Ligero is a light rail transit system in Mexico City that complements the metro and bus networks by serving southern areas of the city.
  • E. Campinas
    Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
  • 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f149bd1c81908ff58ac504ace2bf completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a48a7b71848190ab3e69fc84779301 completed March 1, 2026, 6:50 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.