Triple
T33310299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Valentine |
E852856
|
entity |
| Predicate | hasOriginalProductionLanguage |
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: [Shirley Valentine, hasOriginalProductionLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalProductionLanguage Context triple: [Shirley Valentine, hasOriginalProductionLanguage, English]
-
A.
originalLanguageOfFilmOrTVShow
chosen
Indicates the language in which a film or TV show was originally produced and released.
-
B.
workInOriginalLanguage
Indicates that a work is being created, presented, or studied in the language in which it was originally produced, without translation.
-
C.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
D.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
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.
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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
Created at: May 1, 2026, 1:33 a.m.