Triple

T10633968
Position Surface form Disambiguated ID Type / Status
Subject Coosa River E250529 entity
Predicate crossesCity P13729 FINISHED
Object Wetumpka, Alabama E461265 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: Wetumpka, Alabama | Statement: [Coosa River, crossesCity, Wetumpka, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wetumpka, Alabama
Context triple: [Coosa River, crossesCity, Wetumpka, Alabama]
  • A. Wetumpka, Alabama chosen
    Wetumpka, Alabama is a small city in Elmore County known for its historic sites, including nearby Fort Toulouse-Fort Jackson, and its scenic location along the Coosa River.
  • B. Moody, Alabama
    Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
  • C. Jackson, Alabama
    Jackson, Alabama is a small city in Clarke County known historically as a regional center for timber and paper industries in southwestern Alabama.
  • D. Gadsden, Alabama
    Gadsden, Alabama is a small industrial city in northeastern Alabama known historically for its manufacturing plants and labor history.
  • E. Columbia, Alabama
    Columbia, Alabama is a small town in southeastern Alabama that forms part of the Dothan metropolitan area and is one of the older settlements in Houston County.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfab47bc819086684edc1b6dce74 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a3e0e1481909c277be4c12b46ea completed April 10, 2026, 10:31 p.m.
Created at: April 8, 2026, 9:02 p.m.