Triple
T14224291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yarrangobilly Caves |
E352576
|
entity |
| Predicate | hasThermalPoolTemperature |
P4459
|
FINISHED |
| Object | approximately 27 degrees Celsius |
—
|
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 27 degrees Celsius | Statement: [Yarrangobilly Caves, hasThermalPoolTemperature, approximately 27 degrees Celsius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThermalPoolTemperature Context triple: [Yarrangobilly Caves, hasThermalPoolTemperature, approximately 27 degrees Celsius]
-
A.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
hasThermalCharacteristic
Indicates that an entity possesses a specific thermal property or behavior, such as conductivity, capacity, or response to temperature.
-
C.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
-
D.
hasTemperatureRegime
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
-
E.
containsThermalBath
Indicates that one entity includes or features a thermal bath within its premises or composition.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6227c288819081473ce44f9f0934 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:06 a.m.