Triple

T433979
Position Surface form Disambiguated ID Type / Status
Subject Holmes County, Florida E9772 entity
Predicate hasWaterAreaPercentage P475 FINISHED
Object about 2 percent LITERAL 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: about 2 percent | Statement: [Holmes County, Florida, hasWaterAreaPercentage, about 2 percent]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasWaterAreaPercentage
Context triple: [Holmes County, Florida, hasWaterAreaPercentage, about 2 percent]
  • A. areaWater chosen
    Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
  • B. appliesToWaterBody
    Indicates that something (such as a rule, condition, property, or effect) is relevant or applicable specifically to a particular water body.
  • C. drainageBasinArea
    Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
  • D. locatedInBodyOfWater
    Indicates that an entity is situated within or on the surface of a specific body of water.
  • E. hasMajorLake
    Indicates that a geographic region or area contains at least one significant lake within its boundaries.
  • F. None of above.

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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ef0a008c8190ae0aa25e4df9c35f completed Feb. 28, 2026, 1:35 p.m.
PD Predicate disambiguation batch_69a2edda55e88190b7c17ba94d7df1ce completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.