Triple
T2328787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carménère |
E48352
|
entity |
| Predicate | previousMisidentification |
P28207
|
FINISHED |
| Object | long confused with Merlot in Chile |
—
|
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: long confused with Merlot in Chile | Statement: [Carménère, previousMisidentification, long confused with Merlot in Chile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousMisidentification Context triple: [Carménère, previousMisidentification, long confused with Merlot in Chile]
-
A.
previousClassification
Indicates that one classification precedes another in time or in an ordered sequence of classifications.
-
B.
notableMisconception
chosen
Indicates that a commonly held but incorrect belief or understanding exists about the subject.
-
C.
previousConflict
Indicates that a conflict or dispute occurred between the entities at some earlier time prior to the current context.
-
D.
previouslyObserved
Indicates that the subject entity has been seen, recorded, or encountered at some earlier time prior to the current context.
-
E.
lostRecognitionTo
Indicates that one entity no longer holds a title, status, or recognition because it has been transferred or conceded to another 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abcc30c5e881908c5d526d7e7491d0 |
completed | March 7, 2026, 6:56 a.m. |
| PD | Predicate disambiguation | batch_69abc5926d048190a535e3f23d41de2a |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:50 p.m.