Triple
T20507433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Springs State Park |
E503469
|
entity |
| Predicate | springWaterTemperature |
P123862
|
FINISHED |
| Object | approximately 54 degrees Fahrenheit |
—
|
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 54 degrees Fahrenheit | Statement: [Giant Springs State Park, springWaterTemperature, approximately 54 degrees Fahrenheit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: springWaterTemperature Context triple: [Giant Springs State Park, springWaterTemperature, approximately 54 degrees Fahrenheit]
-
A.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
-
B.
waterTemperatureAtSource
chosen
Indicates the temperature of water measured at its point of origin or source location.
-
C.
waterTemperatureComparedTo
Indicates how the temperature of one body or sample of water compares to the temperature of another.
-
D.
waterTemperatureForSpawning
Indicates the specific water temperature conditions required or suitable for an organism to begin or successfully carry out spawning.
-
E.
densityAt15C
Indicates the material’s density measured specifically at a temperature of 15 degrees Celsius.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc82dd0819085d64d65a1e72c70 |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.