Triple

T6594964
Position Surface form Disambiguated ID Type / Status
Subject Misiones Province E148451 entity
Predicate hasCity P316 FINISHED
Object Posadas E101951 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: Posadas | Statement: [Misiones Province, hasCity, Posadas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Posadas
Context triple: [Misiones Province, hasCity, Posadas]
  • A. Posadas chosen
    Posadas is the capital city of Misiones Province in northeastern Argentina, located on the border with Paraguay.
  • B. Catanduva
    Catanduva is a municipality in the northwestern region of the state of São Paulo, Brazil, known for its agricultural production and regional commercial importance.
  • C. Tandil
    Tandil is a mid-sized city in central Argentina known for its scenic hilly landscapes, stone formations, and tourism-focused outdoor activities.
  • D. Bariloche
    Bariloche is a popular Argentine city in the Andean region known for its lakes, mountains, skiing, and Swiss-style alpine architecture.
  • E. Bahía Blanca
    Bahía Blanca is a major port city in southern Buenos Aires Province, Argentina, known for its industrial activity and strategic location on the Atlantic coast.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aed289448190a13c77085bccb006 completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eedfe3a88190a1d7fda9ff0dc9bd completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:55 p.m.