Triple
T34408573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senator Film |
E883186
|
entity |
| Predicate | languageOfDistribution |
P54680
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Senator Film, languageOfDistribution, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfDistribution Context triple: [Senator Film, languageOfDistribution, German]
-
A.
laterLanguageOfDissemination
Indicates that one language was used to disseminate or publish a work at a later time than another language associated with the same work.
-
B.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
C.
languageOfTransmission
chosen
Indicates the language used to convey or transmit the content or information in a given communication or resource.
-
D.
languageOfProvision
Indicates the language in which a provision, such as a legal or contractual clause, is written or officially expressed.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a00694f72888190983fee7d687a6daa |
completed | May 10, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_6a00685dbf44819098ea0c86bb9e50d8 |
completed | May 10, 2026, 11:13 a.m. |
Created at: May 1, 2026, 1:59 a.m.