Triple
T13241941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Couper |
E315298
|
entity |
| Predicate | hasSpellingVariantStatus |
P85225
|
FINISHED |
| Object | less common than Cooper |
—
|
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: less common than Cooper | Statement: [Couper, hasSpellingVariantStatus, less common than Cooper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpellingVariantStatus Context triple: [Couper, hasSpellingVariantStatus, less common than Cooper]
-
A.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
B.
spellingStatus
Indicates the correctness or condition of the spelling of a given text or term.
-
C.
hasOrthographyStatus
chosen
Indicates the orthographic status or condition of how something is written or spelled, such as its conformity to a particular writing system or standard.
-
D.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
E.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d59e84c8190a9e547d0fe26a5f9 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:23 p.m.