Triple
T22163502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovers of the Arctic Circle |
E547729
|
entity |
| Predicate | producedBy |
P490
|
FINISHED |
| Object | Sogetel |
—
|
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: Sogetel | Statement: [Lovers of the Arctic Circle, producedBy, Sogetel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sogetel Context triple: [Lovers of the Arctic Circle, producedBy, Sogetel]
-
A.
Sogetel
chosen
Sogetel is a film and television production company known for producing European, particularly French-language, cinematic works.
-
B.
Megacom
Megacom is a leading telecommunications company in Kyrgyzstan that provides widespread mobile and internet services across the country.
-
C.
GTE Mobilnet
GTE Mobilnet was a major U.S. cellular telephone service provider that operated mobile networks before eventually becoming part of Verizon Wireless.
-
D.
Mobily
Mobily is a major Saudi Arabian telecommunications company providing mobile and internet services across the Kingdom.
-
E.
Telkom
Telkom is a major South African telecommunications company that provides fixed-line, mobile, and data services across the country.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2f2f90819080b5bb73a6052c24 |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.