Triple

T21220872
Position Surface form Disambiguated ID Type / Status
Subject Terri Sewell E522960 entity
Predicate workLocation P7 FINISHED
Object Birmingham, Alabama NE NERFINISHED

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: Birmingham, Alabama | Statement: [Terri Sewell, workLocation, Birmingham, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Birmingham, Alabama
Context triple: [Terri Sewell, workLocation, Birmingham, Alabama]
  • A. Birmingham, Alabama, United States chosen
    Birmingham, Alabama, United States is a major industrial and cultural city in the American South, historically known for its steel production and pivotal role in the Civil Rights Movement.
  • B. Montgomery, Alabama
    Montgomery, Alabama is the state capital known as a pivotal center of the American civil rights movement, including events such as the Montgomery Bus Boycott.
  • C. Bessemer, Alabama
    Bessemer, Alabama is an industrial city in Jefferson County that forms part of the greater Birmingham region in central Alabama.
  • D. Tuscaloosa, Alabama
    Tuscaloosa, Alabama is a city in western Alabama known as the home of the University of Alabama and a regional center for education, healthcare, and industry.
  • E. Montgomery
    Montgomery is a historic market town in Powys, Wales, known for its medieval castle ruins and Georgian architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73477957081908ab9ad11f51d15fd completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:43 p.m.