Triple
T9573666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biathlon at the 2002 Winter Olympics |
E230988
|
entity |
| Predicate | mainVenueDistanceFromHostCity |
P60767
|
FINISHED |
| Object | about 80 km |
—
|
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: about 80 km | Statement: [Biathlon at the 2002 Winter Olympics, mainVenueDistanceFromHostCity, about 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainVenueDistanceFromHostCity Context triple: [Biathlon at the 2002 Winter Olympics, mainVenueDistanceFromHostCity, about 80 km]
-
A.
distanceFromMajorCity
chosen
Indicates the measured distance between a given location and a specified major city.
-
B.
distanceToAirport
Indicates the measured distance between a given location and the nearest or specified airport.
-
C.
distanceBetweenHomeCities
Indicates the measured spatial distance separating the home cities of two entities.
-
D.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
E.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99a94c788190a4bb5d2b676908ac |
completed | April 1, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:05 p.m.