Triple
T2070181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utah Olympic Oval |
E44797
|
entity |
| Predicate | recordSettingVenueFor |
P35179
|
FINISHED |
| Object | long track speed skating |
—
|
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: long track speed skating | Statement: [Utah Olympic Oval, recordSettingVenueFor, long track speed skating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordSettingVenueFor Context triple: [Utah Olympic Oval, recordSettingVenueFor, long track speed skating]
-
A.
venue
Indicates the place or location where an event, activity, or interaction takes place.
-
B.
notableRecordingVenueFor
Indicates that a venue is particularly recognized or distinguished as the place where a specific recording was made.
-
C.
legacyVenue
Indicates that a venue has historical or long-standing significance, often preserved or recognized due to its past importance or enduring role.
-
D.
usualVenueSince
Indicates that a particular venue has been the regular or customary location for something (e.g., an event or activity) starting from a specified point in time.
-
E.
previousVenue
Indicates that one venue was used or occupied before another in a sequence of venues.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9f677108190aea3c8db7850c892 |
completed | March 7, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69abb7aee9b48190999620176e3a6ee2 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:41 p.m.