Triple

T4217072
Position Surface form Disambiguated ID Type / Status
Subject Place des Arts E94244 entity
Predicate architect P184 FINISHED
Object Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
 E425200 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: Arcop | Statement: [Place des Arts, architect, Arcop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arcop
Context triple: [Place des Arts, architect, Arcop]
  • A. Arcore
    Arcore is a small town in the Lombardy region of northern Italy, known for its historic villas and proximity to Milan.
  • B. Acrivos
    Acrivos is a Greek-origin surname most notably associated with Andreas Acrivos, a prominent chemical engineer and fluid dynamicist.
  • C. Arpoador
    Arpoador is a famous rocky peninsula and beach area in Rio de Janeiro, Brazil, renowned for its surfing waves and sunset views over the ocean.
  • D. Acubens
    Acubens is the traditional name of Alpha Cancri, a multiple star system in the constellation Cancer.
  • E. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • 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: Arcop
Triple: [Place des Arts, architect, Arcop]
Generated description
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arcop
Target entity description: Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
  • A. Arcore
    Arcore is a small town in the Lombardy region of northern Italy, known for its historic villas and proximity to Milan.
  • B. Acrivos
    Acrivos is a Greek-origin surname most notably associated with Andreas Acrivos, a prominent chemical engineer and fluid dynamicist.
  • C. Arpoador
    Arpoador is a famous rocky peninsula and beach area in Rio de Janeiro, Brazil, renowned for its surfing waves and sunset views over the ocean.
  • D. Acubens
    Acubens is the traditional name of Alpha Cancri, a multiple star system in the constellation Cancer.
  • E. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34beb470481909ceff19195417f19 completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a855cfc08190acceced9cb80f41a completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a8e024a081909e7ecbe969793281 completed March 14, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_69b5acefd1f881908226ff68a741552b completed March 14, 2026, 6:46 p.m.
Created at: March 12, 2026, 11:04 p.m.