Triple
T16063030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angrignon |
E389660
|
entity |
| Predicate | fareZone |
P844
|
FINISHED |
| Object | ARTM A |
E808914
|
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: ARTM A | Statement: [Angrignon, fareZone, ARTM A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ARTM A Context triple: [Angrignon, fareZone, ARTM A]
-
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.
ARTM
ARTM is the regional public transit authority responsible for planning, coordinating, and financing metropolitan transportation services in the Greater Montreal area of Quebec, Canada.
-
C.
Allart
Allart is a Dutch given name historically borne by figures such as the 17th-century painter Allart van Everdingen.
-
D.
ARTF
ARTF is Mexico’s federal regulatory agency responsible for overseeing and regulating the country’s railway transportation system.
-
E.
ARTB
ARTB is a U.S. Army training formation responsible for conducting advanced airborne and Ranger courses for soldiers.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837a04108190b5a1dbbe2063039e |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe47ca9748190be24a490c3cf0e8c |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:57 a.m.