Triple

T1349113
Position Surface form Disambiguated ID Type / Status
Subject Baker v. Nelson E28840 entity
Predicate originatingJurisdiction P4507 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: [Baker v. Nelson, originatingJurisdiction, Minnesota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minnesota
Context triple: [Baker v. Nelson, originatingJurisdiction, 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. 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.
  • C. 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.
  • D. North Dakota
    North Dakota is a sparsely populated U.S. state known for its Great Plains landscapes, agricultural economy, and significant oil production from the Bakken formation.
  • E. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its extensive freshwater coastline, automotive industry centered in Detroit, and diverse mix of urban centers and natural landscapes.
  • 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_69a498571d248190a0ac9eb02d97097f completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c268745481908be649526c18e558 completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fae5aa08190b6aa50b543a175b8 completed March 9, 2026, 1:17 a.m.
Created at: March 1, 2026, 7:56 p.m.