Triple
T19148663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Anna |
E468746
|
entity |
| Predicate | hasAlternateLanguagePerformances |
P121206
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Donna Anna, hasAlternateLanguagePerformances, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateLanguagePerformances Context triple: [Donna Anna, hasAlternateLanguagePerformances, German]
-
A.
adaptedInLanguage
chosen
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
B.
hasLanguageOfShows
Indicates that an entity (such as a channel, platform, or schedule) is associated with the language in which its shows are presented.
-
C.
hasAlternateTitleRegion
Indicates that an entity has an alternate title that is specifically used or valid within a particular geographic region.
-
D.
hasIntertitlesLanguage
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
E.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e97b48508190b61458821b6475ad |
completed | April 20, 2026, 8:53 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b475d88190a8c15e8eb01dbfef |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.