Triple

T3434331
Position Surface form Disambiguated ID Type / Status
Subject Lake of the Isles E72410 entity
Predicate hasState P35 FINISHED
Object Minnesota E33799 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: Minnesota | Statement: [Lake of the Isles, hasState, Minnesota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minnesota
Context triple: [Lake of the Isles, hasState, Minnesota]
  • A. Minnesota chosen
    Minnesota is a U.S. state known for its numerous lakes, cold winters, and vibrant cultural and economic centers like Minneapolis–Saint Paul.
  • B. D. Minn.
    D. Minn. is the standard legal abbreviation for the United States District Court for the District of Minnesota, a federal trial court within the Eighth Circuit.
  • C. Minnesota and Wisconsin
    Minnesota and Wisconsin are two neighboring U.S. states in the Upper Midwest, known for their abundant lakes, forests, and shared border along the upper Mississippi River.
  • D. Iowa
    Iowa is a Midwestern U.S. state known for its extensive agriculture, especially corn and soybean production, and its role in national politics through the Iowa caucuses.
  • E. Wisconsin
    Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
  • 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_69ad85af50288190a854b76653deee6f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9c3300881909f5c3544f8923b41 completed March 8, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b367f6bb90819084055d9d001430fd completed March 13, 2026, 1:27 a.m.
Created at: March 8, 2026, 3:16 p.m.