Triple

T13734207
Position Surface form Disambiguated ID Type / Status
Subject Eau Claire County, Wisconsin E329892 entity
Predicate hasRiver P165 FINISHED
Object Eau Claire River E354246 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: Eau Claire River | Statement: [Eau Claire County, Wisconsin, hasRiver, Eau Claire River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eau Claire River
Context triple: [Eau Claire County, Wisconsin, hasRiver, Eau Claire River]
  • A. Eau Claire River chosen
    The Eau Claire River is a tributary in western Wisconsin that flows through the city of Eau Claire before joining the Chippewa River.
  • B. La Crosse River
    The La Crosse River is a tributary of the Mississippi River in western Wisconsin, flowing through Fort McCoy and the city of La Crosse.
  • C. Elm River
    Elm River is a lesser-known tributary waterway that feeds into the James River within its watershed.
  • D. Mukwonago River
    The Mukwonago River is a biologically rich southeastern Wisconsin waterway renowned for its high water quality and diverse native aquatic species.
  • E. Wapsipinicon River
    The Wapsipinicon River is a tributary of the Mississippi River in eastern Iowa, known for its scenic, meandering course and recreational opportunities such as fishing and paddling.
  • 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_69fdf06a3e208190a24e6cd9cb97e99c completed May 8, 2026, 2:17 p.m.
Created at: April 9, 2026, 9:55 p.m.