Triple
T16985256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nałęczów |
E412047
|
entity |
| Predicate | hasTypeOfResort |
P38274
|
FINISHED |
| Object | cardiology spa resort |
—
|
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: cardiology spa resort | Statement: [Nałęczów, hasTypeOfResort, cardiology spa resort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfResort Context triple: [Nałęczów, hasTypeOfResort, cardiology spa resort]
-
A.
hasResortType
chosen
Indicates that an entity (such as a resort or accommodation) is associated with a specific category or type of resort (e.g., beach resort, ski resort, spa resort).
-
B.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
C.
includesResortType
Indicates that one entity contains or offers a specific type or category of resort as part of its overall composition or services.
-
D.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
E.
isResortDestinationFor
Indicates that a place serves as a resort destination specifically intended for or frequented by a particular person, group, or 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d18af95c8190a25ef0614e1a17f3 |
completed | April 18, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.