Triple

T19281700
Position Surface form Disambiguated ID Type / Status
Subject Western Portugal E482203 entity
Predicate includesCity P3207 FINISHED
Object Loures 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: Loures | Statement: [Western Portugal, includesCity, Loures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loures
Context triple: [Western Portugal, includesCity, Loures]
  • A. Loures chosen
    Loures is a suburban municipality in the Lisbon metropolitan area of Portugal, known for its mix of urban and rural zones and its proximity to the capital city.
  • B. Seixal
    Seixal is a municipality on the south bank of the Tagus River in the Lisbon metropolitan area, known as a residential and industrial suburb connected to Lisbon by road and ferry links.
  • C. Seixal
    Seixal is a small coastal town on the north side of Madeira Island in Portugal, known for its dramatic cliffs, natural pools, and black sand beach.
  • D. Lisboa-Oriente
    Lisboa-Oriente is a major intermodal railway and transport hub in Lisbon, Portugal, known for its modern architecture and role as a key gateway for national and international travel.
  • E. Odivelas Municipality
    Odivelas Municipality is a suburban municipality in the Lisbon District of Portugal, known for its dense urban character and integration into the Lisbon metropolitan area.
  • 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_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbff1e6c819094ae6a5ad40adb65 completed April 20, 2026, 10:12 a.m.
Created at: April 10, 2026, 1:30 p.m.