Triple

T1738732
Position Surface form Disambiguated ID Type / Status
Subject Ponta da Piedade E37980 entity
Predicate locatedIn P40 FINISHED
Object southern Portugal E6079 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: southern Portugal | Statement: [Ponta da Piedade, locatedIn, southern Portugal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: southern Portugal
Context triple: [Ponta da Piedade, locatedIn, southern Portugal]
  • A. northeastern Portugal
    Northeastern Portugal is a culturally distinct, sparsely populated region bordering Spain, known for its Mirandese-speaking communities, traditional rural landscapes, and historic towns.
  • B. Algarve chosen
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • C. mainland Portugal
    Mainland Portugal is the continental part of the Portuguese Republic in southwestern Europe, comprising the country’s primary territory on the Iberian Peninsula.
  • D. Alverca do Ribatejo, Portugal
    Alverca do Ribatejo is a suburban city in the Lisbon metropolitan area of Portugal, known for its industrial activity and proximity to the Tagus River.
  • E. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c35aec8190b5c19ace5524173f completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc99a3e908190b64f70cf7ab83ed3 completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:30 p.m.