Triple
T19062446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Évaux-les-Bains |
E466565
|
entity |
| Predicate | usesThermalWatersFor |
P117964
|
FINISHED |
| Object | medical treatments |
—
|
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: medical treatments | Statement: [Évaux-les-Bains, usesThermalWatersFor, medical treatments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesThermalWatersFor Context triple: [Évaux-les-Bains, usesThermalWatersFor, medical treatments]
-
A.
hasThermalWaterUse
Indicates that something makes use of thermal water, typically for purposes such as heating, bathing, energy production, or therapeutic applications.
-
B.
hasThermalBathsSince
Indicates that an entity has had thermal baths available or in operation continuously since a specified point in time.
-
C.
hasNumberOfHotSprings
Indicates the quantity of hot springs associated with a given entity.
-
D.
hasHotSpring
Indicates that one entity possesses, contains, or is associated with a hot spring.
-
E.
hotSpringsUsedFor
chosen
Indicates that hot springs serve a particular purpose or are utilized for a specific activity, function, or benefit.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e195ac048190a57b57e585d022d4 |
completed | April 20, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.