Triple

T22055727
Position Surface form Disambiguated ID Type / Status
Subject Escalabitano E545004 entity
Predicate associatedWithCity P1481 FINISHED
Object Santarém NE NERFINISHED

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: Santarém | Statement: [Escalabitano, associatedWithCity, Santarém]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santarém
Context triple: [Escalabitano, associatedWithCity, Santarém]
  • A. Santarém chosen
    Santarém is a historic Portuguese city in the Ribatejo region, known for its Gothic architecture and strategic position overlooking the Tagus River.
  • B. 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.
  • C. Porto São Bento
    Porto São Bento is a historic railway station in Porto, Portugal, renowned for its ornate azulejo tile panels and central role in the city’s commuter and regional rail network.
  • D. 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.
  • E. Porto dos Casais
    Porto dos Casais was the original colonial settlement that later developed into the Brazilian city of Porto Alegre.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3377c48190890c17407b9527d6 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1285790948190b21abfb09abbb5e5 completed April 28, 2026, 9:36 p.m.
Created at: April 16, 2026, 8:26 p.m.