Triple

T15618687
Position Surface form Disambiguated ID Type / Status
Subject Tallapoosa County, Alabama E375486 entity
Predicate containsPart P35 FINISHED
Object Lake Martin E160029 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: Lake Martin | Statement: [Tallapoosa County, Alabama, containsPart, Lake Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Martin
Context triple: [Tallapoosa County, Alabama, containsPart, Lake Martin]
  • A. Lake Martin chosen
    Lake Martin is a large, man-made reservoir in central Alabama known for its scenic shoreline, recreational boating, and lakeside communities.
  • B. Lake Monroe
    Lake Monroe is a large freshwater lake in central Florida that serves as a prominent widening of the St. Johns River and a key recreational and ecological area.
  • C. Lake Monroe
    Lake Monroe is a large man-made reservoir in south-central Indiana known for boating, fishing, and outdoor recreation.
  • D. Lake Barkley
    Lake Barkley is a large reservoir in western Kentucky and Tennessee known for boating, fishing, and recreation as part of the Land Between the Lakes region.
  • E. Lake Lurleen
    Lake Lurleen is a reservoir in Tuscaloosa County, Alabama, best known as the central feature and namesake of Lake Lurleen State Park.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e997ce481909b2f10d25705fbc6 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff997b9c9081908f6a68e28a50a359 completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 4:13 a.m.