Triple
T12920722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen BWk |
E309110
|
entity |
| Predicate | hasThirdLetterMeaning |
P12765
|
FINISHED |
| Object | k = cold |
—
|
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: k = cold | Statement: [Köppen BWk, hasThirdLetterMeaning, k = cold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThirdLetterMeaning Context triple: [Köppen BWk, hasThirdLetterMeaning, k = cold]
-
A.
hasLastThreeLettersMeaning
Indicates that the last three letters of one entity (typically a word or string) together form a meaningful unit or have a specific semantic significance.
-
B.
hasThirdLetter
chosen
Indicates that a string or sequence possesses a specific character or element in the third position.
-
C.
hasThreeLetterForm
Indicates that an entity’s written or symbolic form consists of exactly three letters.
-
D.
thirdWord
Indicates that one entity is the third word in sequence within another entity (such as a text or phrase).
-
E.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971e7f6e881908c7bb12283898c80 |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:41 p.m.