Triple

T10398568
Position Surface form Disambiguated ID Type / Status
Subject François-Xavier Garneau E245083 entity
Predicate employer P7 FINISHED
Object City of Quebec E7422 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 Quebec | Statement: [François-Xavier Garneau, employer, City of Quebec]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Quebec
Context triple: [François-Xavier Garneau, employer, City of Quebec]
  • A. Quebec City chosen
    Quebec City is the historic capital of the Canadian province of Quebec, renowned for its well-preserved fortified old town and rich French colonial heritage.
  • B. Montreal
    Montreal is the largest city in Quebec, Canada, known for its vibrant bilingual culture, historic architecture, and status as a major economic and cultural center.
  • C. Les Cèdres, Quebec
    Les Cèdres, Quebec is a small municipality in southwestern Quebec, Canada, situated along the Saint Lawrence River west of Montreal.
  • D. Gatineau
    Gatineau is a city in western Quebec, Canada, located across the Ottawa River from Ottawa and forming part of the National Capital Region.
  • E. Downtown Quebec City
    Downtown Quebec City is the historic and commercial core of Quebec City, known for its European-style architecture, government institutions, and vibrant urban life.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d1f2408190beaa8197641c66b4 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d95e5197cc8190ad70c665ec2f8fa8 completed April 10, 2026, 8:32 p.m.
Created at: April 6, 2026, 12:07 p.m.