Triple
T13474001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandcastle 5 Productions |
E318202
|
entity |
| Predicate | associatedWorkCountry |
P835
|
FINISHED |
| Object | British cinema |
—
|
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: British cinema | Statement: [Sandcastle 5 Productions, associatedWorkCountry, British cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWorkCountry Context triple: [Sandcastle 5 Productions, associatedWorkCountry, British cinema]
-
A.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
-
B.
collaborationCountry
Indicates that there is a collaborative relationship or joint activity involving entities associated with the specified country.
-
C.
relatedCountry
chosen
Indicates that there is a relevant or associated relationship between an entity and a specified country, without specifying the exact nature of that relationship.
-
D.
associatedCountryMostProminently
Indicates the country with which an entity is most strongly or prominently associated, relative to any other countries it may be linked to.
-
E.
countryOfEmployer
Indicates the country in which the employer of a given person or entity is based.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2447bc81908baf1f4b55095144 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.