Triple
T4639785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Royal Park |
E101622
|
entity |
| Predicate | hasWinterSports |
P57535
|
FINISHED |
| Object | yes |
—
|
LITERAL 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: yes | Statement: [Mount Royal Park, hasWinterSports, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterSports Context triple: [Mount Royal Park, hasWinterSports, yes]
-
A.
hasWinterSportsSeason
Indicates that an entity participates in, is associated with, or has a defined period for winter sports activities or competitions.
-
B.
hasPopularWinterSports
Indicates that a place or context is associated with winter sports that are widely practiced, enjoyed, or well-attended.
-
C.
hasNightSkiing
Indicates that a location or facility offers skiing activities that take place during nighttime under artificial lighting.
-
D.
hasSnowSportsSchool
Indicates that a place or facility offers an organized school or program for learning and practicing snow sports.
-
E.
hasMountainSport
Indicates that an entity is associated with or offers a particular mountain-related sport or activity.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a8e0ee88190becab97d2ef1571a |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:14 p.m.