Triple

T15818613
Position Surface form Disambiguated ID Type / Status
Subject Thunder Bay City Hall E383542 entity
Predicate operator P179 FINISHED
Object City of Thunder Bay E15925 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: City of Thunder Bay | Statement: [Thunder Bay City Hall, operator, City of Thunder Bay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Thunder Bay
Context triple: [Thunder Bay City Hall, operator, City of Thunder Bay]
  • A. Thunder Bay chosen
    Thunder Bay is a Canadian city in northwestern Ontario that serves as a key transportation, shipping, and commercial hub on the north shore of Lake Superior.
  • B. Thunder Bay
    Thunder Bay is a bay on Lake Huron in Michigan known for its numerous shipwrecks and the Thunder Bay National Marine Sanctuary.
  • C. Fort Frances
    Fort Frances is a small Canadian town in northwestern Ontario located on the Rainy River along the U.S. border opposite International Falls, Minnesota.
  • D. City of Timmins
    The City of Timmins is a mining-centered city in northeastern Ontario, Canada, known for its gold production history and role as a regional service hub.
  • E. City of Algoma
    The City of Algoma is a small lakeside community in northeastern Wisconsin known for its Lake Michigan shoreline, commercial fishing heritage, and local art and tourism.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0c4a552008190863343c9d41ebf3f completed April 16, 2026, 11:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe69332c81909aa57e64de163cbe completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:49 a.m.