Triple

T14564000
Position Surface form Disambiguated ID Type / Status
Subject Siesta Beach E341736 entity
Predicate nearestCity P350 FINISHED
Object Sarasota E68509 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: Sarasota | Statement: [Siesta Beach, nearestCity, Sarasota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarasota
Context triple: [Siesta Beach, nearestCity, Sarasota]
  • A. Sarasota, Florida chosen
    Sarasota, Florida is a Gulf Coast city known for its beaches, arts and cultural scene, and as a longtime hub for Major League Baseball spring training.
  • B. Bonita Springs
    Bonita Springs is a coastal city in southwest Florida known for its Gulf beaches, parks, and resort communities.
  • C. Bradenton
    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.
  • D. Wellington, Florida
    Wellington, Florida is an affluent village in Palm Beach County known as a major international equestrian center and winter polo capital of the world.
  • E. Sanford, Florida
    Sanford, Florida is a historic city in central Florida on the southern shore of Lake Monroe, known as a transportation hub and gateway to the Orlando metropolitan area.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb38afa8881909c9151b7620949ae completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff218b93d48190a7e16c3934828aa8 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 1:23 a.m.