Triple

T15238043
Position Surface form Disambiguated ID Type / Status
Subject 150 North Riverside E364179 entity
Predicate hasView P854 FINISHED
Object Chicago River E13146 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: Chicago River | Statement: [150 North Riverside, hasView, Chicago River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chicago River
Context triple: [150 North Riverside, hasView, Chicago River]
  • A. Chicago River chosen
    The Chicago River is a historically significant waterway in Chicago known for its engineered reversal of flow, its role in the city’s development, and its iconic green dyeing on St. Patrick’s Day.
  • B. Fox River
    The Fox River is a Midwestern U.S. river that flows through Wisconsin and Illinois, supporting numerous communities and ecosystems along its course.
  • C. Fox River
    Fox River is a small, remote community located on Alaska’s Kenai Peninsula, known for its rural lifestyle and surrounding wilderness.
  • D. Lo River
    The Lo River is a significant river in northern Vietnam that flows through mountainous and agricultural regions before joining the Red River system.
  • E. Han River
    The Han River is a major tributary of the Yangtze River in central China, flowing through Hubei province and the city of Wuhan.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007da7e988190925a9b67b8070bc7 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a63464c8190afab59257c6a2095 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:12 a.m.