Triple
T21512247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BWh |
E530754
|
entity |
| Predicate | hasDiurnalRangeCharacteristic |
P25527
|
FINISHED |
| Object | hot days and cool to cold nights |
—
|
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: hot days and cool to cold nights | Statement: [BWh, hasDiurnalRangeCharacteristic, hot days and cool to cold nights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiurnalRangeCharacteristic Context triple: [BWh, hasDiurnalRangeCharacteristic, hot days and cool to cold nights]
-
A.
diurnalRange
chosen
Indicates the difference between the daily maximum and minimum values of a measured quantity, typically temperature, over a 24-hour period.
-
B.
isDiurnal
Indicates that an entity is active during the daytime and rests at night.
-
C.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
-
D.
dayNightVariant
Indicates a relationship where one entity is a day-time version and the other is a night-time version of the same underlying thing.
-
E.
hasSolarDayLength
Indicates that an entity is associated with a specific duration for one complete solar day (the time between successive noons).
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea8779c081908171c58d345d54ae |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.