Triple

T7679001
Position Surface form Disambiguated ID Type / Status
Subject Houston County, Alabama E173939 entity
Predicate hasCommunity P2605 FINISHED
Object Taylor, Alabama E361309 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: Taylor, Alabama | Statement: [Houston County, Alabama, hasCommunity, Taylor, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taylor, Alabama
Context triple: [Houston County, Alabama, hasCommunity, Taylor, Alabama]
  • A. Taylor, Alabama chosen
    Taylor, Alabama is a small town located in southeastern Alabama that is part of the Dothan metropolitan area.
  • B. Tyler, Alabama
    Tyler, Alabama is a small unincorporated rural community located in Dallas County in the central part of the state.
  • C. Steele, Alabama
    Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
  • D. Billingsley, Alabama
    Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
  • E. Townley, Alabama
    Townley, Alabama is a small unincorporated community located in Walker County in the north-central part of the state.
  • 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_69c6995703e0819081de77361b602e78 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701fe2cc88190b5fd5e1378c32e5b completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9cd7f9b2c81908a1f77a9cc37a0be completed March 30, 2026, 1:10 a.m.
Created at: March 27, 2026, 4:01 p.m.