Triple

T1598597
Position Surface form Disambiguated ID Type / Status
Subject South Alabama E34339 entity
Predicate includes P1393 FINISHED
Object Mobile County E129640 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: Mobile County | Statement: [South Alabama, includes, Mobile County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mobile County
Context triple: [South Alabama, includes, Mobile County]
  • A. Mobile County chosen
    Mobile County is a coastal county in southwestern Alabama that includes the city of Mobile and serves as a key economic and cultural hub for the region.
  • B. Winston County
    Winston County is a rural county in northwestern Alabama known historically for its Unionist stance during the Civil War and its location within the state's hill country.
  • C. Wilcox County
    Wilcox County is a rural county in south-central Alabama known for its rich Civil Rights history and location along the Alabama River in the state's Black Belt region.
  • D. Baldwin County, Alabama
    Baldwin County, Alabama is a large Gulf Coast county known for its beaches, bays, and fast-growing communities across Mobile Bay from the city of Mobile.
  • E. Blount County
    Blount County is a county in north-central Alabama known for its rural communities, scenic landscapes, and historic covered bridges.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90948ddb08190a6fc0597198a7946 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0aaae76c81909707184b3a3d87d5 completed March 8, 2026, 11:47 p.m.
Created at: March 4, 2026, 7:27 p.m.