Triple
T29907937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Águas de Março |
E759589
|
entity |
| Predicate | originalLanguageVersionRecordedIn |
P201405
|
FINISHED |
| Object | Brazil |
—
|
NE NERFINISHED |
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: Brazil | Statement: [Águas de Março, originalLanguageVersionRecordedIn, Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageVersionRecordedIn Context triple: [Águas de Março, originalLanguageVersionRecordedIn, Brazil]
-
A.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
B.
originalLanguageOfFilmOrTVShow
Indicates the language in which a film or TV show was originally produced and released.
-
C.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
-
D.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
E.
originalLanguageStatus
Indicates the status or condition of something with respect to its original language (e.g., whether it is in, derived from, or altered from the language in which it was first created).
- F. None of above. chosen
Provenance (4 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fff327d7788190a41ea5cbae060177 |
completed | May 10, 2026, 2:53 a.m. |
Created at: April 29, 2026, 6:09 p.m.