Triple
T22505910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen's Theatre, Haymarket, London |
E556387
|
entity |
| Predicate | languageOfManyLibrettos |
P111046
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Queen's Theatre, Haymarket, London, languageOfManyLibrettos, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfManyLibrettos Context triple: [Queen's Theatre, Haymarket, London, languageOfManyLibrettos, Italian]
-
A.
originalLanguageOfLibretto
Indicates the language in which a libretto was originally written for a given work.
-
B.
librettistNationality
Indicates the relationship between a librettist and the country or nationality with which they are associated.
-
C.
librettoAdaptationToLanguage
chosen
Indicates that a libretto has been adapted or translated into a specific target language.
-
D.
librettistOfOpera
Indicates that one entity is the librettist who wrote the text (libretto) for the specified opera.
-
E.
librettistOfWorkAppearingIn
Indicates that a person is the librettist responsible for the text of a work that appears within a larger composite work or collection.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5bf0f0819093426d83ebd80ef0 |
completed | April 29, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.