Triple
T10676449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pec pod Sněžkou |
E251629
|
entity |
| Predicate | SněžkaStatus |
P95260
|
FINISHED |
| Object | highest mountain of the Czech Republic |
—
|
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: highest mountain of the Czech Republic | Statement: [Pec pod Sněžkou, SněžkaStatus, highest mountain of the Czech Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SněžkaStatus Context triple: [Pec pod Sněžkou, SněžkaStatus, highest mountain of the Czech Republic]
-
A.
skiTouringSeason
Indicates the period of the year during which ski touring activities are typically possible or permitted.
-
B.
distanceToŚnieżka
Indicates the measured or calculated spatial distance from a given entity or location to Śnieżka.
-
C.
skiAreaName
Indicates that an entity has a specific name used to identify a ski area.
-
D.
endPointMountain
Indicates that a path, route, or boundary terminates at a mountain.
-
E.
hasSkiRunsLength_km
Indicates the total length, in kilometers, of the ski runs associated with an entity.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fb94b05c8190b66bf64f5c6d166b |
completed | April 9, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8a93208190a573061387e2aebb |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:09 p.m.