Triple
T11161995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jastrzębie-Zdrój |
E264057
|
entity |
| Predicate | hasHealthResortHistory |
P37550
|
FINISHED |
| Object | spa town origins |
—
|
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: spa town origins | Statement: [Jastrzębie-Zdrój, hasHealthResortHistory, spa town origins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthResortHistory Context triple: [Jastrzębie-Zdrój, hasHealthResortHistory, spa town origins]
-
A.
hasHistoryOf
chosen
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
B.
hasSpaResort
Indicates that one entity possesses, includes, or is associated with a spa resort as an amenity or feature.
-
C.
hasHealthCode
Indicates that an entity is associated with a specific health-related classification or status code.
-
D.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
E.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8832fe88190a74d81f9ed547baa |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.