Triple

T6204426
Position Surface form Disambiguated ID Type / Status
Subject Serra da Ibiapaba E138712 entity
Predicate hasCityOnPlateau P940 FINISHED
Object Tianguá E136536 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: Tianguá | Statement: [Serra da Ibiapaba, hasCityOnPlateau, Tianguá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tianguá
Context triple: [Serra da Ibiapaba, hasCityOnPlateau, Tianguá]
  • A. Tianguá chosen
    Tianguá is a municipality in northeastern Brazil known for its location in the highlands of the state of Ceará and its role as a regional commercial and agricultural center.
  • B. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • C. Horizonte
    Horizonte is a municipality in the state of Ceará in northeastern Brazil, known for its growing industrial sector and proximity to the Fortaleza metropolitan area.
  • D. Tupiza
    Tupiza is a small historic town in southern Bolivia known for its dramatic red-rock canyons and as a gateway to Andean landscapes and mining regions.
  • E. Tiba
    Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
  • 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_69c008acbea48190991c6b834bb45d65 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0626d96ec8190816c00c44668177d completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f412d848190a8e78ad7822aa399 completed March 23, 2026, 4:50 p.m.
Created at: March 22, 2026, 4:20 p.m.