Triple
T13702212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detective Mike Bosko |
E328546
|
entity |
| Predicate | filmOriginalLanguage |
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: [Detective Mike Bosko, filmOriginalLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmOriginalLanguage Context triple: [Detective Mike Bosko, filmOriginalLanguage, English]
-
A.
originalLanguageOfFilmOrTVShow
chosen
Indicates the language in which a film or TV show was originally produced and released.
-
B.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
C.
primaryFilmingLanguage
Indicates the main language in which a film or audiovisual work was originally filmed or recorded.
-
D.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
E.
filmedInLanguage
Indicates that a film or video work was originally recorded using a particular spoken or signed language.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad162158819089280ee1e6b5c2cf |
completed | April 13, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.