Triple
T26366286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Połczyn-Zdrój |
E660341
|
entity |
| Predicate | hasTypeOfTreatment |
P122242
|
FINISHED |
| Object | balneotherapy |
—
|
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: balneotherapy | Statement: [Połczyn-Zdrój, hasTypeOfTreatment, balneotherapy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfTreatment Context triple: [Połczyn-Zdrój, hasTypeOfTreatment, balneotherapy]
-
A.
hasReceivedTreatmentFor
Indicates that an entity has undergone or been given a treatment in relation to a specified condition, issue, or problem.
-
B.
treatmentType
chosen
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
-
C.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
D.
hasSubjectTreatment
Indicates that a subject is receiving, has received, or is associated with a particular treatment or therapeutic intervention.
-
E.
usesTreatment
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
- 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_69ee8126d52c8190bc0b34337c2c9aa8 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 26, 2026, 10:55 p.m.