Triple

T11223427
Position Surface form Disambiguated ID Type / Status
Subject Townley, Alabama E265630 entity
Predicate abbreviation P43 FINISHED
Object Townley, AL E265630 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: Townley, AL | Statement: [Townley, Alabama, abbreviation, Townley, AL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Townley, AL
Context triple: [Townley, Alabama, abbreviation, Townley, AL]
  • A. Townley, Alabama chosen
    Townley, Alabama is a small unincorporated community located in Walker County in the north-central part of the state.
  • B. Ensley, Alabama
    Ensley, Alabama is a historic industrial neighborhood in Birmingham that developed as a major steelmaking and manufacturing center in the late 19th and early 20th centuries.
  • C. Talucah, Alabama
    Talucah, Alabama is an unincorporated rural community located in Morgan County in northern Alabama.
  • D. Summerfield, Alabama
    Summerfield, Alabama is a rural unincorporated community in Dallas County known for its historic character and agricultural surroundings in the central part of the state.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8ec8fb08190b27144ab65f85957 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4978389848190ac5a8b985bbea15f completed April 19, 2026, 8:51 a.m.
Created at: April 8, 2026, 9:30 p.m.