Triple
T15980384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte-Vertu |
E387555
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object |
ARTM
ARTM is the regional public transit authority responsible for planning, coordinating, and funding mass transit services across the Greater Montreal area in Quebec, Canada.
|
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 | Statement: [Côte-Vertu, fareSystem, ARTM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ARTM Context triple: [Côte-Vertu, fareSystem, ARTM]
-
A.
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.
-
B.
ARTF
ARTF is Mexico’s federal regulatory agency responsible for overseeing and regulating the country’s railway transportation system.
-
C.
ARTV
ARTV is a Canadian French-language specialty television channel focused on arts and culture programming.
-
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.
Allart
Allart is a Dutch given name historically borne by figures such as the 17th-century painter Allart van Everdingen.
- 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 Triple: [Côte-Vertu, fareSystem, ARTM]
Generated description
ARTM is the regional public transit authority responsible for planning, coordinating, and funding mass transit services across the Greater Montreal area in Quebec, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ARTM Target entity description: ARTM is the regional public transit authority responsible for planning, coordinating, and funding mass transit services across the Greater Montreal area in Quebec, Canada.
-
A.
ARTM A
chosen
ARTM A is a central fare zone within the Autorité régionale de transport métropolitain’s public transit system in the Greater Montreal area.
-
B.
ARTF
ARTF is Mexico’s federal regulatory agency responsible for overseeing and regulating the country’s railway transportation system.
-
C.
ARTV
ARTV is a Canadian French-language specialty television channel focused on arts and culture programming.
-
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.
Allart
Allart is a Dutch given name historically borne by figures such as the 17th-century painter Allart van Everdingen.
- F. None of above.
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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157542cd88190832e7ae79bd38ffc |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cb0ed48190b35c19f3961f183b |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc5f664148190a1f400c28d31cafe |
completed | May 9, 2026, 11:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc6f9b4f4819092600165241377f6 |
completed | May 9, 2026, 11:44 p.m. |
Created at: April 10, 2026, 4:54 a.m.