Triple

T23554572
Position Surface form Disambiguated ID Type / Status
Subject Wainfleet E578146 entity
Predicate hasRegionCode P3446 FINISHED
Object Niagara
Niagara is a regional municipality in Ontario, Canada, known for encompassing the famous Niagara Falls and surrounding communities.
 E854965 NE FINISHED

How this triple was built (4 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 | Statement: [Wainfleet, hasRegionCode, Niagara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Niagara
Context triple: [Wainfleet, hasRegionCode, Niagara]
  • A. Niagara
    Niagara is a small rural city located in Grand Forks County in the U.S. state of North Dakota.
  • B. 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.
  • C. Niagara
    Niagara is the codename for Sun Microsystems' UltraSPARC T1 multicore, multithreaded server processor designed for high-throughput, low-power computing.
  • D. Niagara
    "Niagara" is a track by Barbra Streisand featured on her 1979 disco-influenced album "Wet."
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Niagara
Triple: [Wainfleet, hasRegionCode, Niagara]
Generated description
Niagara is a regional municipality in Ontario, Canada, known for encompassing the famous Niagara Falls and surrounding communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Niagara
Target entity description: Niagara is a regional municipality in Ontario, Canada, known for encompassing the famous Niagara Falls and surrounding communities.
  • A. Niagara chosen
    Niagara is a regional municipality in southern Ontario, Canada, known for encompassing the famous Niagara Falls and surrounding communities.
  • B. Niagara
    Niagara is a small rural city located in Grand Forks County in the U.S. state of North Dakota.
  • C. 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.
  • D. Niagara
    Niagara is an American singer and visual artist best known as the charismatic frontwoman of the Detroit proto-punk band Destroy All Monsters.
  • E. Niagara
    Niagara is the codename for Sun Microsystems' UltraSPARC T1 multicore, multithreaded server processor designed for high-throughput, low-power computing.
  • F. None of above.

Provenance (5 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_69e245fa93448190919cb04534560542 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1aed253788190ba75109af0e91b37 completed April 29, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0cdf67efbc8190a75c1d6cb9bd63f9 completed May 19, 2026, 10:08 p.m.
NEDg Description generation batch_6a0ce12579188190befd636d3714675a completed May 19, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_6a0ce187efa48190876f67fef4873af2 completed May 19, 2026, 10:17 p.m.
Created at: April 17, 2026, 6:12 p.m.