Triple

T13734562
Position Surface form Disambiguated ID Type / Status
Subject Jon Mueller E329902 entity
Predicate basedIn P40 FINISHED
Object Wisconsin E16627 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: Wisconsin | Statement: [Jon Mueller, basedIn, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wisconsin
Context triple: [Jon Mueller, basedIn, Wisconsin]
  • A. Wisconsin chosen
    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.
  • B. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its automotive industry, extensive freshwater coastline, and major cities like Detroit and Grand Rapids.
  • C. 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 forests, rivers, and outdoor recreation areas.
  • D. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its automotive industry, extensive freshwater coastline, and manufacturing heritage.
  • E. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its automotive industry, extensive freshwater coastline, and two distinct peninsulas.
  • 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_69d80772315881908f980cae40d91664 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de0201d3c48190aa306be231a28bc1 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79d66cb088190be2621753d0a6740 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:55 p.m.