Triple
T8107765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Escamillo |
E189268
|
entity |
| Predicate | languageOfOpera |
P26614
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Escamillo, languageOfOpera, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOpera Context triple: [Escamillo, languageOfOpera, French]
-
A.
originalLanguageOfLibretto
Indicates the language in which a libretto was originally written for a given work.
-
B.
languageOfMusic
chosen
Indicates that a specified language is used in, associated with, or characteristic of a particular piece of music or musical work.
-
C.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, or context).
-
D.
operaAct
Indicates that an entity performs in or takes part in an act (segment) of an opera performance.
-
E.
broadwayAdaptationLanguage
Indicates the language in which a Broadway adaptation of a work is performed or produced.
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42fa40e08190955fccec1a28eb34 |
completed | March 31, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69cb04a2ed1c8190b73562321ad688bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:32 p.m.