Triple
T9505999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Bachelor ski area |
E229269
|
entity |
| Predicate | hasNordicCenter |
P88444
|
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 Bachelor ski area, hasNordicCenter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNordicCenter Context triple: [Mount Bachelor ski area, hasNordicCenter, yes]
-
A.
hasRAndDCenterIn
Indicates that an entity maintains a research and development (R&D) center located in a specified place.
-
B.
hasCulturalCentre
Indicates that one entity possesses, hosts, or contains a cultural centre associated with it.
-
C.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
D.
hasCircuitCentre
Indicates that an entity has, is associated with, or is organized around a specific circuit center that serves as its focal or central point.
-
E.
hasCentralLandmark
Indicates that a place or area contains a primary or defining landmark located at or near its center.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9852b7e48190a8f69cbde10d2858 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:57 p.m.