Triple

T9598097
Position Surface form Disambiguated ID Type / Status
Subject Square Victoria–OACI station E231782 entity
Predicate fareZone P844 FINISHED
Object ARTM A
ARTM A is a central fare zone within the Autorité régionale de transport métropolitain’s public transit system in the Greater Montreal area.
 E808914 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: ARTM A | Statement: [Square Victoria–OACI station, fareZone, ARTM A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ARTM A
Context triple: [Square Victoria–OACI station, fareZone, ARTM A]
  • A. Allart
    Allart is a Dutch given name historically borne by figures such as the 17th-century painter Allart van Everdingen.
  • B. ARTB
    ARTB is a U.S. Army training formation responsible for conducting advanced airborne and Ranger courses for soldiers.
  • C. Artěl
    Artěl was a Czech artists' and designers' cooperative active in the early 20th century that promoted modern applied arts and design.
  • D. ARTs
    ARTs are dual-status civilian and military personnel who provide full-time support to the U.S. Air Force Reserve by maintaining readiness, training, and continuity for reserve units.
  • E. ART Area
    The ART Area is the Applications and Real-Time area within the IETF that oversees working groups focused on application-layer protocols and real-time communication technologies.
  • 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: ARTM A
Triple: [Square Victoria–OACI station, fareZone, ARTM A]
Generated description
ARTM A is a central fare zone within the Autorité régionale de transport métropolitain’s public transit system in the Greater Montreal area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ARTM A
Target entity description: ARTM A is a central fare zone within the Autorité régionale de transport métropolitain’s public transit system in the Greater Montreal area.
  • A. Allart
    Allart is a Dutch given name historically borne by figures such as the 17th-century painter Allart van Everdingen.
  • B. ARTB
    ARTB is a U.S. Army training formation responsible for conducting advanced airborne and Ranger courses for soldiers.
  • C. Artěl
    Artěl was a Czech artists' and designers' cooperative active in the early 20th century that promoted modern applied arts and design.
  • D. ARTs
    ARTs are dual-status civilian and military personnel who provide full-time support to the U.S. Air Force Reserve by maintaining readiness, training, and continuity for reserve units.
  • E. ART Area
    The ART Area is the Applications and Real-Time area within the IETF that oversees working groups focused on application-layer protocols and real-time communication technologies.
  • 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_69ca8484838c8190b2049199d22fef70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a366d3481908db62e476958eafe completed April 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1619f4170819092ae90b2896b0855 completed April 4, 2026, 7:08 p.m.
NEDg Description generation batch_69d163c1abfc8190baae07681ea13104 completed April 4, 2026, 7:17 p.m.
NED2 Entity disambiguation (via description) batch_69d16476b9188190ab28efb0433c99b0 completed April 4, 2026, 7:20 p.m.
Created at: March 30, 2026, 8:07 p.m.