Triple
T26323781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen Dwa |
E662189
|
entity |
| Predicate | secondLetterMeaning |
P50619
|
FINISHED |
| Object | dry winter |
—
|
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: dry winter | Statement: [Köppen Dwa, secondLetterMeaning, dry winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondLetterMeaning Context triple: [Köppen Dwa, secondLetterMeaning, dry winter]
-
A.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
B.
secondLetterRepresents
chosen
Indicates that the second letter of one entity stands for, symbolizes, or denotes another entity or concept.
-
C.
secondPartMeaning
Indicates that something represents the latter or subsequent portion of a larger whole in terms of its meaning or semantic content.
-
D.
secondWord
Indicates that one entity is the second word in sequence immediately following the first entity in a text or utterance.
-
E.
secondLetterMatches
Indicates that the second character of one string or sequence is the same as the second character of another string or sequence.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 26, 2026, 10:29 p.m.