Triple

T21156400
Position Surface form Disambiguated ID Type / Status
Subject Ontario E521321 entity
Predicate containsWaterBody P1778 FINISHED
Object Niagara River NE NERFINISHED

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: Niagara River | Statement: [Ontario, containsWaterBody, Niagara River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niagara River
Context triple: [Ontario, containsWaterBody, Niagara River]
  • A. Niagara River chosen
    The Niagara River is a short but powerful river in North America that flows from Lake Erie to Lake Ontario and is renowned for forming the famous Niagara Falls along the U.S.–Canada border.
  • B. Niagara
    Niagara is a 1953 film noir thriller starring Marilyn Monroe, noted for its dramatic use of the Niagara Falls setting and Monroe’s breakout femme fatale performance.
  • C. Niagara
    Niagara is a small rural city located in Grand Forks County in the U.S. state of North Dakota.
  • D. Niagara
    Niagara is a cold-hardy, labrusca-based white grape variety widely grown in the eastern United States, known for its distinctive “foxy” aroma and use in sweet and table wines.
  • E. Niagara
    Niagara is an American singer and visual artist best known as the charismatic frontwoman of the Detroit proto-punk band Destroy All Monsters.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50d1ea481909c07e63c3ead9316 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7252c6db08190bcdffc3f2cfc6138 completed April 21, 2026, 7:20 a.m.
Created at: April 16, 2026, 2:59 p.m.