Triple

T9222308
Position Surface form Disambiguated ID Type / Status
Subject Alentejo Central E221591 entity
Predicate contains P35 FINISHED
Object Vendas Novas E380682 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: Vendas Novas | Statement: [Alentejo Central, contains, Vendas Novas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vendas Novas
Context triple: [Alentejo Central, contains, Vendas Novas]
  • A. Vendas Novas chosen
    Vendas Novas is a Portuguese town and municipality in the Alentejo region, known for its strategic location between Lisbon and Évora and its traditional bifanas (pork sandwiches).
  • B. Currais Novos
    Currais Novos is a municipality in the interior of the Brazilian state of Rio Grande do Norte, known for its semi-arid climate, livestock farming, and mineral resources.
  • C. Morada Nova
    Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
  • D. Morrinhos
    Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
  • E. Valinhos
    Valinhos is a municipality in southeastern Brazil known for its agricultural production, especially grapes and figs, and its proximity to the city of Campinas.
  • 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda76e3648190af9e24381db7679a completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d066384a908190b833d4ae5b3c5074 completed April 4, 2026, 1:15 a.m.
Created at: March 30, 2026, 7:28 p.m.