Triple
T27726822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koněprusy Caves |
E697322
|
entity |
| Predicate | hasVerticalExtent |
P10733
|
FINISHED |
| Object | about 70 meters |
—
|
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 70 meters | Statement: [Koněprusy Caves, hasVerticalExtent, about 70 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerticalExtent Context triple: [Koněprusy Caves, hasVerticalExtent, about 70 meters]
-
A.
verticalExtent
chosen
Indicates the total height or vertical span of an entity or region from its lowest to highest point.
-
B.
hasVerticalSection
Indicates that one entity possesses or includes a distinct vertical section or segment as part of its structure or representation.
-
C.
hasHeight
Indicates that one entity possesses a specific vertical measurement or stature.
-
D.
hasSignificantHeight
Indicates that one entity’s height is notably large or substantial relative to a given standard or to other entities.
-
E.
hasVerticalAxisRelation
Indicates that one entity is positioned, aligned, or related to another along the vertical axis (up-down direction).
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 3:09 p.m.