Triple
T20486653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pirita Beach |
E502611
|
entity |
| Predicate | typicalWaterTemperatureInSummer |
P118798
|
FINISHED |
| Object | around 18–20 °C |
—
|
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: around 18–20 °C | Statement: [Pirita Beach, typicalWaterTemperatureInSummer, around 18–20 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWaterTemperatureInSummer Context triple: [Pirita Beach, typicalWaterTemperatureInSummer, around 18–20 °C]
-
A.
hasAverageSummerWaterTemperature
chosen
Indicates that an entity is associated with a specific mean water temperature measured over the summer season.
-
B.
averageSummerTemperatureC
Indicates the typical or mean air temperature, measured in degrees Celsius, experienced at a location during the summer season.
-
C.
waterTemperatureComparedTo
Indicates how the temperature of one body or sample of water compares to the temperature of another.
-
D.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
E.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b5b96c0819080c47064143cdbc9 |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
Created at: April 16, 2026, 11:34 a.m.