Triple
T18112806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Then She Found Me |
E433521
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | ThinkFilm |
—
|
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: ThinkFilm | Statement: [Then She Found Me, distributor, ThinkFilm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ThinkFilm Context triple: [Then She Found Me, distributor, ThinkFilm]
-
A.
ThinkFilm
chosen
ThinkFilm was an independent film distribution company known for releasing arthouse and specialty films in the early 2000s.
-
B.
Alliance Films
Alliance Films was a major Canadian film distribution and production company known for releasing a wide range of independent and international movies in Canada and other markets.
-
C.
Tartan Films
Tartan Films was a UK-based independent film distribution company known for releasing cult, arthouse, and international cinema, particularly Asian extreme films.
-
D.
Icon Films
Icon Films is a British television production company known for creating popular factual and wildlife documentary series, including the hit show "River Monsters."
-
E.
Rook Films
Rook Films is a British independent film production company known for its distinctive, often surreal and genre-bending movies.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd3fd9c81909bfe95927f7553e3 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.