Triple

T15640987
Position Surface form Disambiguated ID Type / Status
Subject Calos E376062 entity
Predicate principalTownOf P383 FINISHED
Object Calusa E77086 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: Calusa | Statement: [Calos, principalTownOf, Calusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calusa
Context triple: [Calos, principalTownOf, Calusa]
  • A. Calusa chosen
    The Calusa were a powerful Indigenous people of southwest Florida known for their complex chiefdom, maritime culture, and resistance to European colonization.
  • B. Tequesta
    The Tequesta were a Native American people who inhabited the southeastern coast of Florida, particularly around present-day Miami and the Florida Keys, prior to European contact.
  • C. Tocobaga
    The Tocobaga were a Native American people who inhabited the Tampa Bay region of Florida prior to European contact.
  • D. Opa-locka
    Opa-locka is a city in Miami-Dade County, Florida, known for its distinctive Moorish Revival architecture and themed street names inspired by the tales of One Thousand and One Nights.
  • E. Tequesta, Florida
    Tequesta, Florida is a small coastal village in northern Palm Beach County known for its affluent residential communities, waterfront lifestyle, and proximity to beaches and natural waterways.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed06b388190bfebb77fe70e7df1 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6790f2288190add8ab0bc0f114bf completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 4:15 a.m.