Triple
T9895262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Climatron |
E181553
|
entity |
| Predicate | humidityRange |
P91032
|
FINISHED |
| Object | high humidity |
—
|
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: high humidity | Statement: [Climatron, humidityRange, high humidity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humidityRange Context triple: [Climatron, humidityRange, high humidity]
-
A.
growthTemperatureRange
Indicates the range of temperatures within which an organism or entity can grow or function effectively.
-
B.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
C.
temperatureRangeDifference
Indicates the difference between two temperature ranges, typically measuring how much one range is higher or lower than another.
-
D.
hasTemperatureRegime
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
-
E.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
- F. None of above. chosen
Provenance (4 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4a89e148190901753e67483d72c |
completed | April 2, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69cd1d872d50819096b7ab166a8decf1 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:39 p.m.