Triple
T30065334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarandilla de la Vera |
E764016
|
entity |
| Predicate | hasParadorHotel |
P195771
|
FINISHED |
| Object | Parador de Jarandilla de la Vera |
—
|
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: Parador de Jarandilla de la Vera | Statement: [Jarandilla de la Vera, hasParadorHotel, Parador de Jarandilla de la Vera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParadorHotel Context triple: [Jarandilla de la Vera, hasParadorHotel, Parador de Jarandilla de la Vera]
-
A.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
B.
hasPartnerHotel
Indicates that one hotel has an established partnership or affiliation relationship with another hotel.
-
C.
hasMountainHotel
Indicates that a location or region contains or is associated with a hotel situated in a mountainous area.
-
D.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
E.
hasSpaResort
Indicates that one entity possesses, includes, or is associated with a spa resort as an amenity or feature.
- 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fde5d7d9548190880a9d95b8f0f66b |
completed | May 8, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69fde4e1bf9c81909754545275eccc03 |
completed | May 8, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69fde5d677b88190bc904e6df8617c18 |
completed | May 8, 2026, 1:32 p.m. |
Created at: April 29, 2026, 6:59 p.m.