Triple

T1742016
Position Surface form Disambiguated ID Type / Status
Subject Georgia Gold Belt E38253 entity
Predicate containsCity P294 FINISHED
Object Carrollton E163434 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: Carrollton | Statement: [Georgia Gold Belt, containsCity, Carrollton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carrollton
Context triple: [Georgia Gold Belt, containsCity, Carrollton]
  • A. Carrollton
    Carrollton is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities, business parks, and convenient access to major highways.
  • B. Carrollton chosen
    Carrollton is a city in western Georgia that serves as a regional hub for education, commerce, and culture.
  • C. Conroe
    Conroe is a city in southeastern Texas, United States, located north of Houston and known for its rapid growth and proximity to Lake Conroe.
  • D. Rowlett
    Rowlett is a suburban city in the Dallas–Fort Worth metropolitan area of Texas, known for its location along Lake Ray Hubbard and family-oriented residential communities.
  • E. Duncanville
    Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c6d21c8190809bedaa798e2b14 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaca5f348190a8c1be9948d960e6 completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:30 p.m.