Triple
T28331743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | étude |
E717553
|
entity |
| Predicate | hasNotableExampleSet |
P61425
|
FINISHED |
| Object | Chopin Études, Op. 10 |
—
|
NE NERFINISHED |
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: Chopin Études, Op. 10 | Statement: [étude, hasNotableExampleSet, Chopin Études, Op. 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableExampleSet Context triple: [étude, hasNotableExampleSet, Chopin Études, Op. 10]
-
A.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
hasNotableUseExample
Indicates that there exists a particularly significant or illustrative example of how something is used.
-
C.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
D.
hasNotableWorkExample
chosen
Indicates that an entity has a specific notable work cited as an example associated with it.
-
E.
hasNotableWorkSetThere
Indicates that a notable work (such as a book, film, or other creative piece) is set in or takes place within the referenced location.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
Created at: April 28, 2026, 12:32 a.m.