Triple

T21213352
Position Surface form Disambiguated ID Type / Status
Subject Cartaxo E522773 entity
Predicate borderedBy P224 FINISHED
Object Azambuja 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: Azambuja | Statement: [Cartaxo, borderedBy, Azambuja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azambuja
Context triple: [Cartaxo, borderedBy, Azambuja]
  • A. Azambuja chosen
    Azambuja is a municipality in Portugal known for its agricultural landscape and proximity to the Lisbon metropolitan area.
  • B. Luso
    Luso is a Portuguese civil parish in the municipality of Mealhada, known for its mineral water springs and proximity to the Bussaco Forest.
  • C. Luso
    Luso is the former colonial-era name of the city now known as Luena, the capital of Moxico Province in eastern Angola.
  • D. Itumbiara
    Itumbiara is a municipality in the Brazilian state of Goiás, known for its strategic location on the Paranaíba River and its role as a regional economic and transportation hub.
  • E. Fajão
    Fajão is a small village in central Portugal, situated in the mountainous region of the Arganil municipality.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7347088488190aa764b3f4bbac44d completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:38 p.m.