Triple
T23607413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bela-Bela |
E582934
|
entity |
| Predicate | hasHotSpringTemperature |
P4459
|
FINISHED |
| Object | approximately 52 degrees Celsius at source |
—
|
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: approximately 52 degrees Celsius at source | Statement: [Bela-Bela, hasHotSpringTemperature, approximately 52 degrees Celsius at source]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotSpringTemperature Context triple: [Bela-Bela, hasHotSpringTemperature, approximately 52 degrees Celsius at source]
-
A.
hasHotSpring
Indicates that one entity possesses, contains, or is associated with a hot spring.
-
B.
hasMineralSpringsTemperatureRange
Indicates the range of temperatures characteristic of the mineral springs associated with an entity.
-
C.
hasNumberOfHotSprings
Indicates the quantity of hot springs associated with a given entity.
-
D.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
-
E.
isHot
Indicates that an entity has a high temperature or is perceived as very warm.
- 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0f107048190b81eade6a50db2da |
completed | April 29, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:44 p.m.