Triple
T16656747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tofana |
E404749
|
entity |
| Predicate | willBeVenueFor |
P112843
|
FINISHED |
| Object | 2026 Winter Olympics alpine skiing events |
—
|
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: 2026 Winter Olympics alpine skiing events | Statement: [Tofana, willBeVenueFor, 2026 Winter Olympics alpine skiing events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: willBeVenueFor Context triple: [Tofana, willBeVenueFor, 2026 Winter Olympics alpine skiing events]
-
A.
hasVenueFor
chosen
Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
-
B.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
C.
connectsToEventVenue
Indicates that one entity serves as a link or route providing access or connection to an event venue.
-
D.
isRegularVenueFor
Indicates that a location is commonly or routinely used as the venue for a particular event, activity, or entity’s gatherings.
-
E.
venue
Indicates the place or location where an event, activity, or interaction takes place.
- F. None of above.
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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfb2b308190bf3559df9fbb126f |
completed | April 18, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.