Triple

T19404941
Position Surface form Disambiguated ID Type / Status
Subject Taguspark campus E485427 entity
Predicate region P40 FINISHED
Object Greater Lisbon 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: Greater Lisbon | Statement: [Taguspark campus, region, Greater Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater Lisbon
Context triple: [Taguspark campus, region, Greater Lisbon]
  • A. Lisbon metropolitan area chosen
    The Lisbon metropolitan area is Portugal’s largest urban region, centered on the capital city of Lisbon and encompassing its surrounding municipalities as a major hub of culture, economy, and transportation.
  • B. Coimbra metropolitan area
    The Coimbra metropolitan area is an urban and economic region in central Portugal centered on the historic city of Coimbra and its surrounding municipalities.
  • C. Metropolitan Portugal
    Metropolitan Portugal is the European mainland portion of the Portuguese state, distinct from its overseas territories and regions.
  • D. Lisbon–Porto
    Lisbon–Porto is the main intercity rail corridor in Portugal, linking the capital Lisbon with the northern city of Porto.
  • E. Lisbon–Guimarães
    Lisbon–Guimarães is a major intercity rail route in Portugal connecting the capital Lisbon with the historic northern city of Guimarães.
  • 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6257a361c8190bf019fc350faa225 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.