Triple

T20833496
Position Surface form Disambiguated ID Type / Status
Subject Paseo de la Virgen del Puerto E512893 entity
Predicate hasPublicTransportAccess P3791 FINISHED
Object Principe Pío station NE NERFINISHED

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: Principe Pío station | Statement: [Paseo de la Virgen del Puerto, hasPublicTransportAccess, Principe Pío station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Principe Pío station
Context triple: [Paseo de la Virgen del Puerto, hasPublicTransportAccess, Principe Pío station]
  • A. Príncipe Pío station chosen
    Príncipe Pío station is a major intermodal transport hub in Madrid, Spain, combining commuter rail, metro, and bus services in a historic former railway terminal.
  • B. Mabillon station
    Mabillon station is a Paris Métro station in the 6th arrondissement, serving the Saint-Germain-des-Prés area on the Left Bank.
  • C. Plaza Miserere station
    Plaza Miserere station is a major Buenos Aires Underground stop on Line A that serves the busy Once railway and commercial district.
  • D. Ris-Orangis station
    Ris-Orangis station is a suburban railway station in the Île-de-France region of France that serves the commune of Ris-Orangis on the RER network.
  • E. Parc station
    Parc station is a metro stop on the Charleroi Metro network in Charleroi, Belgium.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32554648190bd66ac99b3a9072b completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.