Triple
T31074094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Třeboň |
E791902
|
entity |
| Predicate | hasSpaSpecialization |
P192148
|
FINISHED |
| Object | treatment of musculoskeletal disorders |
—
|
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: treatment of musculoskeletal disorders | Statement: [Třeboň, hasSpaSpecialization, treatment of musculoskeletal disorders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpaSpecialization Context triple: [Třeboň, hasSpaSpecialization, treatment of musculoskeletal disorders]
-
A.
hasSpaService
Indicates that an entity offers or provides spa-related services or treatments to another entity or for its use.
-
B.
hasSpaType
Indicates that an entity is associated with, or classified by, a specific type or category of spa.
-
C.
hasSpaBrand
Indicates that an entity is associated with or offers services under a particular spa brand.
-
D.
hasSpaResort
Indicates that one entity possesses, includes, or is associated with a spa resort as an amenity or feature.
-
E.
hasSpaStatusLocation
Indicates that an entity has a specific spa-related status associated with a particular location.
- 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_69f224ccdbbc81909b0cdb4cc2d70c7a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
| PDg | Predicate description generation | batch_69fcf82405c88190a19cecf8e9cc272d |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 29, 2026, 9:01 p.m.