Triple
T37358592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leporello |
E927518
|
entity |
| Predicate | hasComicDuetWith |
P76526
|
FINISHED |
| Object | Don Giovanni |
E272018
|
NE 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: Don Giovanni | Statement: [Leporello, hasComicDuetWith, Don Giovanni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComicDuetWith Context triple: [Leporello, hasComicDuetWith, Don Giovanni]
-
A.
hasComicSeries
Indicates that one entity is the comic series to which another entity belongs or with which it is associated.
-
B.
partnerInComedyDuo
chosen
Indicates that two entities are partners together in a comedy duo act or performance team.
-
C.
hasDubActor
Indicates that one entity serves as the dubbing voice actor for another entity in a particular work or version.
-
D.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
E.
comicColorist
Indicates the relationship in which a person serves as the colorist for a comic, responsible for adding color to its artwork.
- F. None of above.
Provenance (4 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_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40afcc8f3c819086297e0621e54f97 |
completed | June 28, 2026, 5:23 a.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.