Triple

T10573190
Position Surface form Disambiguated ID Type / Status
Subject US 31 E249544 entity
Predicate hasTerminus P388 FINISHED
Object Mobile, Alabama E34031 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, Alabama | Statement: [US 31, hasTerminus, Mobile, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mobile, Alabama
Context triple: [US 31, hasTerminus, Mobile, Alabama]
  • A. Mobile, Alabama chosen
    Mobile, Alabama is a historic port city on the Gulf Coast known for its colonial heritage, shipbuilding industry, and hosting one of the oldest Mardi Gras celebrations in the United States.
  • B. Moody, Alabama
    Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
  • C. 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.
  • D. Enterprise, Alabama
    Enterprise, Alabama is a prominent city in southeastern Alabama known for its agricultural heritage and the famous Boll Weevil Monument.
  • E. Columbia, Alabama
    Columbia, Alabama is a small town in southeastern Alabama that forms part of the Dothan metropolitan area and is one of the older settlements in Houston County.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5274929cc81909a79d5e2049f7389 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9988fca088190b13b651985677a6a completed April 11, 2026, 12:40 a.m.
Created at: April 6, 2026, 12:37 p.m.