Triple

T10630010
Position Surface form Disambiguated ID Type / Status
Subject Warren Township E250426 entity
Predicate hasName P744 FINISHED
Object Warren Township E250426 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: Warren Township | Statement: [Warren Township, hasName, Warren Township]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Township
Context triple: [Warren Township, hasName, Warren Township]
  • A. Warren Township chosen
    Warren Township is a rural civil township located within Poweshiek County in the U.S. state of Iowa.
  • B. Winfield Township
    Winfield Township is a local governmental subdivision, likely in the United States, responsible for providing municipal services and administration to residents within its township boundaries.
  • C. Hilliard Township
    Hilliard Township is a small rural municipality located within Ontario’s Timiskaming District in Canada.
  • D. Wilkins Township
    Wilkins Township is a suburban municipality in Allegheny County, Pennsylvania, located just east of Pittsburgh.
  • E. Laird Township
    Laird Township is a small rural municipality in Ontario, Canada, located near Sault Ste. Marie in the Algoma District.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df93a2b88190a0f3a52b8e88f54f completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96babc290819096c0c914d038ba01 completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 9 p.m.