Triple
T23749328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakey Peak |
E586913
|
entity |
| Predicate | hasTypicalWaterTemperatureRange |
P54564
|
FINISHED |
| Object | warm tropical water |
—
|
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: warm tropical water | Statement: [Lakey Peak, hasTypicalWaterTemperatureRange, warm tropical water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWaterTemperatureRange Context triple: [Lakey Peak, hasTypicalWaterTemperatureRange, warm tropical water]
-
A.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
B.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
C.
hasAverageSummerWaterTemperature
Indicates that an entity is associated with a specific mean water temperature measured over the summer season.
-
D.
waterTemperatureComparedTo
Indicates how the temperature of one body or sample of water compares to the temperature of another.
-
E.
hasTemperatureRegime
chosen
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
- 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_69e24908efb08190bf755c3a9b91f222 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcc118dc8190b0b92e402b9a7dd4 |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:13 p.m.