Triple

T5719434
Position Surface form Disambiguated ID Type / Status
Subject Abrantes E126104 entity
Predicate historicalProvince P915 FINISHED
Object Ribatejo E123602 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: Ribatejo | Statement: [Abrantes, historicalProvince, Ribatejo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ribatejo
Context triple: [Abrantes, historicalProvince, Ribatejo]
  • A. Ribatejo chosen
    Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
  • B. Moncalvo
    Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
  • C. Báguanos
    Báguanos is a municipality in eastern Cuba located in the province of Holguín, known for its agricultural activities and rural communities.
  • D. Tabasalu
    Tabasalu is a small town in northern Estonia that serves as the main local hub for the surrounding Harku Parish near the capital, Tallinn.
  • E. Bassignana
    Bassignana is a municipality in the Piedmont region of northern Italy, situated near the confluence of the Tanaro and Po rivers.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e1ec7c8190a08e1b7954db2a9d completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07df49eb881908189fc8afb2ed478 completed March 22, 2026, 11:40 p.m.
Created at: March 22, 2026, 3:46 p.m.