Triple
T19244824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Třeboň |
E481221
|
entity |
| Predicate | hasRegionSpecialty |
P21480
|
FINISHED |
| Object | pond-based landscape |
—
|
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: pond-based landscape | Statement: [Třeboň, hasRegionSpecialty, pond-based landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionSpecialty Context triple: [Třeboň, hasRegionSpecialty, pond-based landscape]
-
A.
specializationRegion
Indicates that something is specialized, adapted, or specifically applicable to a particular geographic or spatial region.
-
B.
regionSpecialization
chosen
Indicates that a region is designated or recognized as being particularly focused on, adapted to, or specialized in a specific function, activity, or domain.
-
C.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
D.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
E.
includedSpecialRegionType
Indicates that a special or designated region is included within another region or context, specifying the type of that included special region.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf47820819081e8b6af852bb1dd |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.