Triple
T6943125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mikado |
E160725
|
entity |
| Predicate | originalRunLanguage |
P58177
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [The Mikado, originalRunLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalRunLanguage Context triple: [The Mikado, originalRunLanguage, English]
-
A.
originalLanguageOfFilmOrTVShow
chosen
Indicates the language in which a film or TV show was originally produced and released.
-
B.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
C.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
D.
originalLanguageSupport
Indicates that one entity provides or maintains functionality, content, or interaction in the original language of another entity.
-
E.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e0c74fe48190aeaa018631e52ef6 |
completed | March 27, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bd5a388190a57a96d925696ff6 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.