Triple

T5867492
Position Surface form Disambiguated ID Type / Status
Subject IMG Academy Bradenton E130431 entity
Predicate city P40 FINISHED
Object Bradenton E216136 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: Bradenton | Statement: [IMG Academy Bradenton, city, Bradenton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bradenton
Context triple: [IMG Academy Bradenton, city, Bradenton]
  • A. Bradenton chosen
    Bradenton is a city on Florida’s Gulf Coast known for its waterfront location along the Manatee River and proximity to popular beaches and the Sarasota–Bradenton metropolitan area.
  • B. Bonita Springs
    Bonita Springs is a coastal city in southwest Florida known for its Gulf beaches, parks, and resort communities.
  • C. Hernando
    Hernando is the Spanish form of the given name Ferdinand, historically borne by several notable figures including explorers and monarchs.
  • D. Cape Coral
    Cape Coral is a rapidly growing coastal city in southwest Florida known for its extensive canal system and waterfront living.
  • E. Pasco
    Pasco is a city in southeastern Washington State that forms part of the Tri-Cities region along with Kennewick and Richland.
  • 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_69c0085047dc8190af24e311edad3c07 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035c27e708190b46c707d61c78877 completed March 22, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1d0c5a88190be8dee862e71a0f6 completed March 23, 2026, 2:13 a.m.
Created at: March 22, 2026, 3:56 p.m.