Triple
T36501379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 173 |
E899337
|
entity |
| Predicate | winterMaintenanceBy |
P185776
|
FINISHED |
| Object | Ministère des Transports du Québec or its contractors |
—
|
NE NERFINISHED |
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: Ministère des Transports du Québec or its contractors | Statement: [Route 173, winterMaintenanceBy, Ministère des Transports du Québec or its contractors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterMaintenanceBy Context triple: [Route 173, winterMaintenanceBy, Ministère des Transports du Québec or its contractors]
-
A.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
B.
winterSeason
Indicates that the time, event, or condition occurs during or is specifically associated with the winter season.
-
C.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
D.
winterAccessMode
Indicates how access to something is configured, permitted, or restricted specifically during the winter season.
-
E.
winterSession
Indicates that an event, course, or activity takes place during a designated winter academic or seasonal session.
- F. None of above. chosen
Provenance (4 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:10 p.m.