Triple
T22998698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polar Circles |
E572577
|
entity |
| Predicate | relatedToPhenomenon |
P137709
|
FINISHED |
| Object | seasonal variation in 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: seasonal variation in daylight | Statement: [Polar Circles, relatedToPhenomenon, seasonal variation in daylight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToPhenomenon Context triple: [Polar Circles, relatedToPhenomenon, seasonal variation in daylight]
-
A.
hasAssociatedPhenomenon
chosen
Indicates that one entity is linked to, or typically occurs together with, a particular phenomenon or observable event.
-
B.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
C.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
encounteredPhenomenon
Indicates that an entity has come across, experienced, or observed a particular phenomenon.
-
E.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f54ce88190930530958e2a1830 |
completed | April 29, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.