Triple
T1386312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Pole |
E29853
|
entity |
| Predicate | dayLengthInSummer |
P2027
|
FINISHED |
| Object | about 6 months of continuous daylight |
—
|
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: about 6 months of continuous daylight | Statement: [South Pole, dayLengthInSummer, about 6 months of continuous daylight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dayLengthInSummer Context triple: [South Pole, dayLengthInSummer, about 6 months of continuous daylight]
-
A.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
-
B.
hasSolarDayLength
chosen
Indicates that an entity is associated with a specific duration for one complete solar day (the time between successive noons).
-
C.
summerTimeZone
Indicates that a specified region or entity uses a particular time zone during the summer or daylight-saving period.
-
D.
timeInWinter
Indicates that the specified time interval occurs during the winter season.
-
E.
differenceFromLondonTimeInSummer
Indicates the time difference between a given location and London during the summer (daylight saving) period.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c339f3d481909c04b14129899945 |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.