Triple
T36843228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Archena |
E910464
|
entity |
| Predicate | spaWatersType |
P167515
|
FINISHED |
| Object | thermal mineral-medicinal waters |
—
|
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: thermal mineral-medicinal waters | Statement: [City of Archena, spaWatersType, thermal mineral-medicinal waters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spaWatersType Context triple: [City of Archena, spaWatersType, thermal mineral-medicinal waters]
-
A.
hasSpaType
Indicates that an entity is associated with, or classified by, a specific type or category of spa.
-
B.
waterParkType
Indicates the specific type or category of a water park associated with an entity.
-
C.
surfSpotType
Indicates the type or category of a surf spot based on its wave or break characteristics.
-
D.
spaName
Indicates that an entity has the specified name of a spa or wellness facility.
-
E.
thermalWaterType
chosen
Indicates the specific classification or type of thermal water associated with an 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_69f76e7f65a881908651b702da592b6d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.