Triple

T1196764
Position Surface form Disambiguated ID Type / Status
Subject Ceará E25684 entity
Predicate hasCity P316 FINISHED
Object Baturité
Baturité is a municipality in the state of Ceará in northeastern Brazil, known for its mountainous terrain and relatively mild climate.
 E136538 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: Baturité | Statement: [Ceará, hasCity, Baturité]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Baturité
Context triple: [Ceará, hasCity, Baturité]
  • A. Hoverla
    Hoverla is the tallest mountain in Ukraine, located in the Carpathian range and popular for hiking and tourism.
  • B. Donuzlav
    Donuzlav is a deep-water lagoon and naval harbor in western Crimea that serves as a strategic base for Russian Black Sea naval operations.
  • C. Mutnovsky
    Mutnovsky is an active stratovolcano on Russia’s Kamchatka Peninsula, known for its frequent eruptions, geothermal activity, and dramatic volcanic landscapes.
  • D. Kalderash
    Kalderash are a prominent subgroup of the Roma people, traditionally known as itinerant metalworkers and craftsmen spread across Eastern and Central Europe and beyond.
  • E. Syvash
    Syvash is a large, shallow system of highly saline lagoons on the western coast of the Sea of Azov, bordering Crimea and known for its marshy, mudflat landscape.
  • 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: Baturité
Triple: [Ceará, hasCity, Baturité]
Generated description
Baturité is a municipality in the state of Ceará in northeastern Brazil, known for its mountainous terrain and relatively mild climate.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Baturité
Target entity description: Baturité is a municipality in the state of Ceará in northeastern Brazil, known for its mountainous terrain and relatively mild climate.
  • A. Hoverla
    Hoverla is the tallest mountain in Ukraine, located in the Carpathian range and popular for hiking and tourism.
  • B. Donuzlav
    Donuzlav is a deep-water lagoon and naval harbor in western Crimea that serves as a strategic base for Russian Black Sea naval operations.
  • C. Mutnovsky
    Mutnovsky is an active stratovolcano on Russia’s Kamchatka Peninsula, known for its frequent eruptions, geothermal activity, and dramatic volcanic landscapes.
  • D. Kalderash
    Kalderash are a prominent subgroup of the Roma people, traditionally known as itinerant metalworkers and craftsmen spread across Eastern and Central Europe and beyond.
  • E. Syvash
    Syvash is a large, shallow system of highly saline lagoons on the western coast of the Sea of Azov, bordering Crimea and known for its marshy, mudflat landscape.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9a305c819091513394f1b67784 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7658cae8819081da26480926ff83 completed March 7, 2026, 7:02 p.m.
NEDg Description generation batch_69ac770141a88190b71552d46fb4d2ad completed March 7, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac777a7768819098b9d4dd771a6750 completed March 7, 2026, 7:07 p.m.
Created at: March 1, 2026, 7:46 p.m.