Triple

T12546673
Position Surface form Disambiguated ID Type / Status
Subject Huguley, Alabama E299985 entity
Predicate hasName P744 FINISHED
Object Huguley, Alabama E299985 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: Huguley, Alabama | Statement: [Huguley, Alabama, hasName, Huguley, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huguley, Alabama
Context triple: [Huguley, Alabama, hasName, Huguley, Alabama]
  • A. Huguley, Alabama chosen
    Huguley, Alabama is a small unincorporated community located in eastern Alabama near the Georgia state line.
  • B. Haleburg, Alabama
    Haleburg, Alabama is a small rural town located in southeastern Alabama near the Georgia state line.
  • C. Townley, Alabama
    Townley, Alabama is a small unincorporated community located in Walker County in the north-central part of the state.
  • D. Heflin, Alabama
    Heflin, Alabama is a small city in Cleburne County that serves as the county seat and lies in eastern Alabama near the Georgia state line.
  • E. 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.
  • 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_69d6ada707008190aaec1238117c9379 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9547f9a1c81908f54c58a116a8446 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a16408081909097d7e3ab750a27 completed May 3, 2026, 8:40 a.m.
Created at: April 8, 2026, 9:57 p.m.