Triple

T5791921
Position Surface form Disambiguated ID Type / Status
Subject Niagara Falls region E128414 entity
Predicate contains P35 FINISHED
Object Niagara Falls E10589 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: Niagara Falls | Statement: [Niagara Falls region, contains, Niagara Falls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niagara Falls
Context triple: [Niagara Falls region, contains, Niagara Falls]
  • A. Niagara Falls chosen
    Niagara Falls is a famous group of massive waterfalls on the border between the United States and Canada, renowned for their impressive volume and natural beauty.
  • B. Horseshoe Falls
    Horseshoe Falls is a distinct curved segment of Victoria Falls known for its dramatic, horseshoe-shaped curtain of water.
  • C. Horseshoe Falls
    Horseshoe Falls is the largest and most famous of the three waterfalls that collectively form Niagara Falls, straddling the border between Canada and the United States.
  • D. The Falls
    The Falls is a novel by Joyce Carol Oates that explores the aftermath of a tragic event at Niagara Falls and its impact on a family over several decades.
  • E. 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.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5870b88190bbfaac2782635128 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09824c7f0819095565e0f29b3a508 completed March 23, 2026, 1:32 a.m.
Created at: March 22, 2026, 3:51 p.m.