Triple

T17249505
Position Surface form Disambiguated ID Type / Status
Subject Dão River E418712 entity
Predicate region P40 FINISHED
Object Centro Region E76433 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: Centro Region | Statement: [Dão River, region, Centro Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Centro Region
Context triple: [Dão River, region, Centro Region]
  • A. Centro Region chosen
    The Centro Region is an administrative region in central Portugal known for its historic cities, universities, and diverse landscapes ranging from Atlantic coastline to mountainous interiors.
  • B. Litoral region
    The Litoral region is a northeastern area of Argentina along major rivers that historically served as a key economic and strategic corridor, especially during 19th-century conflicts.
  • C. Costa Grande region
    The Costa Grande region is a coastal area in the Mexican state of Guerrero known for its beaches, fishing communities, and agricultural production.
  • D. Norte Region
    Norte Region is the northernmost administrative region of Portugal, known for its historic cities like Porto and Braga, rich cultural heritage, and strong industrial and academic presence.
  • E. Oeste Subregion
    Oeste Subregion is an administrative and statistical region in western Portugal known for its coastal landscapes, agriculture, and growing urban centers within the Lisbon metropolitan area.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e2636f48190b29548ff80402bef completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170f96e548190be92846e072118f9 completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.