Triple

T2180346
Position Surface form Disambiguated ID Type / Status
Subject Valcartier, Quebec E49026 entity
Predicate hasNameInLanguage P15 FINISHED
Object Valcartier
Valcartier is a locality in Quebec, Canada, best known for its large Canadian Forces military base and nearby recreational facilities.
 E241326 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: Valcartier | Statement: [Valcartier, Quebec, hasNameInLanguage, Valcartier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Valcartier
Context triple: [Valcartier, Quebec, hasNameInLanguage, Valcartier]
  • A. Desmarais
    Desmarais is a French surname, often associated with notable families and individuals in business, politics, and the arts.
  • B. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • C. Mont-Royal
    Mont-Royal is a prominent hill and urban park in Montreal, Quebec, known for its panoramic city views and central role in the city's identity.
  • D. Pessamit
    Pessamit is a major Innu First Nation community in Quebec, Canada, known for its strong preservation of Innu culture and language.
  • E. Quesnel
    Quesnel is a small city in central British Columbia, Canada, known historically as a Cariboo Gold Rush hub and a regional center for the forestry industry.
  • 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: Valcartier
Triple: [Valcartier, Quebec, hasNameInLanguage, Valcartier]
Generated description
Valcartier is a locality in Quebec, Canada, best known for its large Canadian Forces military base and nearby recreational facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Valcartier
Target entity description: Valcartier is a locality in Quebec, Canada, best known for its large Canadian Forces military base and nearby recreational facilities.
  • A. Desmarais
    Desmarais is a French surname, often associated with notable families and individuals in business, politics, and the arts.
  • B. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • C. Mont-Royal
    Mont-Royal is a prominent hill and urban park in Montreal, Quebec, known for its panoramic city views and central role in the city's identity.
  • D. Pessamit
    Pessamit is a major Innu First Nation community in Quebec, Canada, known for its strong preservation of Innu culture and language.
  • E. Quesnel
    Quesnel is a small city in central British Columbia, Canada, known historically as a Cariboo Gold Rush hub and a regional center for the forestry industry.
  • F. None of above. chosen

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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbef0e2f0819080ca457fe3b8b419 completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5da5930c819087e71a609f76e269 completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5e4a45a08190bd96af6cda06ab35 completed March 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae5ec4a35c8190bffc7a183497e764 completed March 9, 2026, 5:46 a.m.
Created at: March 4, 2026, 7:45 p.m.