Triple
T37358802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fin ch’han dal vino |
E927523
|
entity |
| Predicate | characterNameInScore |
P36851
|
FINISHED |
| Object | Don Giovanni |
—
|
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: Don Giovanni | Statement: [Fin ch’han dal vino, characterNameInScore, Don Giovanni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterNameInScore Context triple: [Fin ch’han dal vino, characterNameInScore, Don Giovanni]
-
A.
scoredForCharacter
Indicates that one entity achieved or recorded a score on behalf of, or associated with, a particular character.
-
B.
characterName
chosen
Indicates that an entity has a specific name used to identify its character.
-
C.
characterSetName
Indicates the name assigned to a particular character set used for encoding or representing characters.
-
D.
characterGivenName
Indicates that a specified given (first) name is assigned to or borne by a particular character.
-
E.
isScoreForCharacter
Indicates that a given score value is associated with, or belongs to, a particular character.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
Created at: May 3, 2026, 4:16 p.m.