Triple

T6632194
Position Surface form Disambiguated ID Type / Status
Subject Piauí E149952 entity
Predicate hasCity P316 FINISHED
Object Floriano
Floriano is a municipality in the Brazilian state of Piauí, known as an important commercial and cultural center in the region.
E598851 NE FINISHED

How this triple was built (4 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: Floriano | Statement: [Piauí, hasCity, Floriano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Floriano
Context triple: [Piauí, hasCity, Floriano]
  • A. Gusmão
    Gusmão is a Portuguese-origin surname notably borne by East Timorese independence leader and statesman Kay Rala Xanana Gusmão.
  • B. Bissaya Barreto
    Bissaya Barreto was a prominent Portuguese physician, professor, and politician known for his influential social and educational initiatives in the Coimbra region.
  • C. Delmiro Gouveia
    Delmiro Gouveia is a municipality in northeastern Brazil known for its historical association with early industrial development and the pioneering entrepreneur Delmiro Augusto da Cruz Gouveia.
  • D. Amílcar Falcão
    Amílcar Falcão is a Portuguese academic and pharmacist who serves as rector of the historic University of Coimbra.
  • E. Manuel dos Santos
    Manuel dos Santos is a former Brazilian professional footballer best known for his time as a forward with Santos FC and the Brazil national team.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Floriano
Triple: [Piauí, hasCity, Floriano]
Generated description
Floriano is a municipality in the Brazilian state of Piauí, known as an important commercial and cultural center in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Floriano
Target entity description: Floriano is a municipality in the Brazilian state of Piauí, known as an important commercial and cultural center in the region.
  • A. Gusmão
    Gusmão is a Portuguese-origin surname notably borne by East Timorese independence leader and statesman Kay Rala Xanana Gusmão.
  • B. Bissaya Barreto
    Bissaya Barreto was a prominent Portuguese physician, professor, and politician known for his influential social and educational initiatives in the Coimbra region.
  • C. Delmiro Gouveia
    Delmiro Gouveia is a municipality in northeastern Brazil known for its historical association with early industrial development and the pioneering entrepreneur Delmiro Augusto da Cruz Gouveia.
  • D. Amílcar Falcão
    Amílcar Falcão is a Portuguese academic and pharmacist who serves as rector of the historic University of Coimbra.
  • E. Manuel dos Santos
    Manuel dos Santos is a former Brazilian professional footballer best known for his time as a forward with Santos FC and the Brazil national team.
  • F. None of above. chosen

Provenance (5 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afc9138c81909d228ce4936d6b8b completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbf329f08190a3f29c4d4c6aa136 completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd0bb0e48190ae51fde4b4631f65 completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd90b9208190b4c5bf44db073314 completed March 27, 2026, 6:33 p.m.
Created at: March 27, 2026, 1:59 p.m.