Triple
T13778325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chernobyl |
E331069
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Sister Pictures |
E860489
|
NE 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: Sister Pictures | Statement: [Chernobyl, productionCompany, Sister Pictures]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sister Pictures Context triple: [Chernobyl, productionCompany, Sister Pictures]
-
A.
Sister Pictures
chosen
Sister Pictures is a British television production company known for creating high-profile, critically acclaimed drama series.
-
B.
Two Brothers Pictures
Two Brothers Pictures is a British television production company known for creating acclaimed drama series such as "Fleabag" and "The Missing."
-
C.
Siren Pictures
Siren Pictures is a South Korean television and film production company best known internationally for producing the hit Netflix series "Squid Game."
-
D.
Blossom Films
Blossom Films is a film and television production company founded by actress Nicole Kidman, known for developing high-profile, character-driven projects.
-
E.
Sycamore Pictures
Sycamore Pictures is an American film production company known for financing and producing independent and mid-budget feature films.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0239cbfc81909064ac2457fdfff5 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07460c081908b3836a3ec382961 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.