Triple

T8604435
Position Surface form Disambiguated ID Type / Status
Subject Vidigueira E203761 entity
Predicate borderedBy P224 FINISHED
Object Serpa E195642 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: Serpa | Statement: [Vidigueira, borderedBy, Serpa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serpa
Context triple: [Vidigueira, borderedBy, Serpa]
  • A. Serpa chosen
    Serpa is a historic walled town and municipality in Portugal’s Alentejo region, known for its medieval architecture, whitewashed houses, and traditional cheese production.
  • B. Abrantes
    Abrantes is a historic Portuguese city in the Santarém District, known for its hilltop castle and strategic location overlooking the Tagus River.
  • C. Gouveia
    Gouveia is a municipality and town in central Portugal, situated in the Serra da Estrela mountain range and known for its natural landscapes and wool industry heritage.
  • D. Golegã
    Golegã is a Portuguese town famed for its equestrian traditions and annual horse fair, located in the Centro Region of Portugal.
  • E. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46dd8ff8819081ef269192047488 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbb11140819081bde8a1565aad4a completed April 2, 2026, 6:55 p.m.
Created at: March 30, 2026, 6:24 p.m.