Triple
T19057928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austria and Slovakia |
E466446
|
entity |
| Predicate | closestCapitalDistanceKmApprox |
P10889
|
FINISHED |
| Object | 55 |
—
|
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: 55 | Statement: [Austria and Slovakia, closestCapitalDistanceKmApprox, 55]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestCapitalDistanceKmApprox Context triple: [Austria and Slovakia, closestCapitalDistanceKmApprox, 55]
-
A.
distanceFromCapital
chosen
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
countryCapitalNearby
Indicates that a country’s capital city is geographically close to a specified location or entity.
-
C.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
D.
nearestCapitalCity
Indicates that one city is the geographically closest capital city to a given location or entity compared to all other capital cities.
-
E.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc0742288190a594be859184841a |
completed | April 20, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.