Triple
T34250420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Il cappello di paglia di Firenze |
E878720
|
entity |
| Predicate | operaAdaptationLanguage |
P121206
|
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: [Il cappello di paglia di Firenze, operaAdaptationLanguage, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaAdaptationLanguage Context triple: [Il cappello di paglia di Firenze, operaAdaptationLanguage, Italian]
-
A.
operaLanguage
Indicates the language in which an opera is written or performed.
-
B.
broadwayAdaptationLanguage
Indicates the language in which a Broadway adaptation of a work is performed or produced.
-
C.
librettoAdaptationToLanguage
Indicates that a libretto has been adapted or translated into a specific target language.
-
D.
adaptedInLanguage
chosen
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
E.
operaLibrettistOfAdaptation
Indicates that one entity is the librettist who wrote the text for an operatic adaptation of another work.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a00acf86e4081909aad9356650e0f79 |
completed | May 10, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_6a00ac813fd08190a0a7782609e74e70 |
completed | May 10, 2026, 4:04 p.m. |
Created at: May 1, 2026, 1:56 a.m.