Triple

T7405390
Position Surface form Disambiguated ID Type / Status
Subject northwestern Tunisia E170856 entity
Predicate hasCity P316 FINISHED
Object Beja E39302 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: Beja | Statement: [northwestern Tunisia, hasCity, Beja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beja
Context triple: [northwestern Tunisia, hasCity, Beja]
  • A. Beja
    The Beja are a traditionally pastoralist Cushitic-speaking ethnic group of northeastern Africa, primarily inhabiting the Red Sea coastal and desert regions of Sudan and neighboring countries.
  • B. Mértola
    Mértola is a historic riverside town and municipality in southeastern Portugal known for its well-preserved medieval architecture and rich Islamic and Roman heritage.
  • C. Beja District chosen
    Beja District is an administrative district in southern Portugal, known for its vast agricultural plains and the historic city of Beja as its capital.
  • D. Santarém
    Santarém is a historic Portuguese city in the Ribatejo region, known for its Gothic architecture and strategic position overlooking the Tagus River.
  • E. Santarém
    Santarém is a Brazilian city in the state of Pará, known for its location at the confluence of the Amazon and Tapajós rivers and its striking “meeting of the waters” phenomenon.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f271f1d481909a46d50b13b51a62 completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8111540f08190919bc9d9670f5ef2 completed March 28, 2026, 5:34 p.m.
Created at: March 27, 2026, 3:10 p.m.