Triple
T26323782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen Dwa |
E662189
|
entity |
| Predicate | thirdLetterMeaning |
P47684
|
FINISHED |
| Object | hot summer |
—
|
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 summer | Statement: [Köppen Dwa, thirdLetterMeaning, hot summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdLetterMeaning Context triple: [Köppen Dwa, thirdLetterMeaning, hot summer]
-
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.
letterMeaning
chosen
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
C.
hasThirdLetter
Indicates that a string or sequence possesses a specific character or element in the third position.
-
D.
thirdWord
Indicates that one entity is the third word in sequence within another entity (such as a text or phrase).
-
E.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
- 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_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 26, 2026, 10:29 p.m.