Triple
T29529791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonio |
E749165
|
entity |
| Predicate | operaLibrettists |
P134607
|
FINISHED |
| Object | Jules-Henri Vernoy de Saint-Georges |
—
|
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: Jules-Henri Vernoy de Saint-Georges | Statement: [Tonio, operaLibrettists, Jules-Henri Vernoy de Saint-Georges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaLibrettists Context triple: [Tonio, operaLibrettists, Jules-Henri Vernoy de Saint-Georges]
-
A.
librettistOfOpera
chosen
Indicates that one entity is the librettist who wrote the text (libretto) for the specified opera.
-
B.
operaLibrettistOfAdaptation
Indicates that one entity is the librettist who wrote the text for an operatic adaptation of another work.
-
C.
composerOfOpera
Indicates that one entity is the composer who created the opera represented by the other entity.
-
D.
librettistOfWorkAppearingIn
Indicates that a person is the librettist responsible for the text of a work that appears within a larger composite work or collection.
-
E.
librettistNationality
Indicates the relationship between a librettist and the country or nationality with which they are associated.
- 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_69f0bd46d99c81908ba9d01cc1dbef7d |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
Created at: April 28, 2026, 4:51 p.m.