Triple

T11890187
Position Surface form Disambiguated ID Type / Status
Subject Auburn-Opelika metropolitan area E282890 entity
Predicate containsCommunity P8617 FINISHED
Object Waverly, Alabama E296726 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: Waverly, Alabama | Statement: [Auburn-Opelika metropolitan area, containsCommunity, Waverly, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waverly, Alabama
Context triple: [Auburn-Opelika metropolitan area, containsCommunity, Waverly, Alabama]
  • A. Waverly, Alabama chosen
    Waverly, Alabama is a small rural town in eastern Alabama known for its tight-knit community and historic Southern character.
  • B. Riverside, Alabama
    Riverside, Alabama is a small community in St. Clair County known for its location along the Coosa River in central Alabama.
  • C. Weaver, Alabama
    Weaver, Alabama is a small city in northeastern Alabama known as a residential community within the Anniston–Oxford metropolitan area.
  • D. Webb, Alabama
    Webb, Alabama is a small town located in southeastern Alabama within the Dothan metropolitan area.
  • E. Courtland, Alabama
    Courtland, Alabama is a small historic town in northern Alabama known for its 19th-century architecture and role in the region’s early transportation and cotton economy.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a3f7548190adfb567f060a175a completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f66849ba888190a50c5a5fcdb935e0 completed May 2, 2026, 9:10 p.m.
Created at: April 8, 2026, 9:44 p.m.