Triple
T8152640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gioachino Rossini |
E190366
|
entity |
| Predicate | numberOfOperasComposed |
P71947
|
FINISHED |
| Object | around 39 |
—
|
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: around 39 | Statement: [Gioachino Rossini, numberOfOperasComposed, around 39]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOperasComposed Context triple: [Gioachino Rossini, numberOfOperasComposed, around 39]
-
A.
estimatedNumberOfOperas
chosen
Indicates the approximate count of operas associated with an entity, rather than an exact, verified number.
-
B.
numberOfConcertosComposed
Indicates the total count of concertos that an entity has composed.
-
C.
numberOfSymphonies
Indicates the total count of symphonies associated with a given entity.
-
D.
partOfComposerOeuvre
Indicates that a musical work belongs to and is included within the overall body of compositions created by a particular composer.
-
E.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d4494c8190aad2ee302e90670f |
completed | March 31, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:37 p.m.