Triple
T20183429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killing Zoe |
E492790
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | October Films |
—
|
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: October Films | Statement: [Killing Zoe, distributor, October Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: October Films Context triple: [Killing Zoe, distributor, October Films]
-
A.
October Films
chosen
October Films was an American independent film distribution company known for releasing critically acclaimed arthouse and foreign films in the 1990s.
-
B.
September Films
September Films is a British television and film production company known for creating reality, entertainment, and documentary programming for international audiences.
-
C.
Ten Films
Ten Films is a film production company known for producing the movie "Samba."
-
D.
Max Films
Max Films is a Canadian film production company known for producing independent and auteur-driven movies.
-
E.
ArenaFilm
ArenaFilm is an Australian film production company known for producing the critically acclaimed drama "Romulus, My Father."
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668f068748190a0941e98ef5afd59 |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.