Triple
T26539705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Hameln-Pyrmont |
E671349
|
entity |
| Predicate | hasHealthResort |
P19664
|
FINISHED |
| Object | Bad Pyrmont |
—
|
NE NERFINISHED |
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: Bad Pyrmont | Statement: [district of Hameln-Pyrmont, hasHealthResort, Bad Pyrmont]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthResort Context triple: [district of Hameln-Pyrmont, hasHealthResort, Bad Pyrmont]
-
A.
hasSpaResort
Indicates that one entity possesses, includes, or is associated with a spa resort as an amenity or feature.
-
B.
hasResortCenter
Indicates that an entity includes or is associated with a resort facility serving as a central location for leisure or vacation activities.
-
C.
hasPopularResort
Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
-
D.
hasSpaTown
chosen
Indicates that a place is associated with or contains a town known for its spa or therapeutic bathing facilities.
-
E.
isThermalResort
Indicates that a place functions as a thermal resort, offering access to natural thermal waters and related wellness or recreational services.
- 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_69eeb3206e748190b90c85cc81f38c91 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 27, 2026, 1:40 a.m.