Triple
T9778067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Holmes |
E237294
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | AI Film |
E452296
|
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: AI Film | Statement: [Mr. Holmes, productionCompany, AI Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AI Film Context triple: [Mr. Holmes, productionCompany, AI Film]
-
A.
AI-Film
chosen
AI-Film is a film production company known for its involvement in notable independent and biographical movies such as "I, Tonya."
-
B.
FilmEngine
FilmEngine is an American film production company known for developing and producing feature films such as the crime thriller "Lucky Number Slevin."
-
C.
Making Movies
Making Movies is a widely respected memoir and craft-focused book in which acclaimed film director Sidney Lumet explains his practical approach to filmmaking.
-
D.
Agfa film production
Agfa film production was a major photographic film manufacturing operation historically associated with the German company Agfa, known for producing widely used camera and motion picture films.
-
E.
ARRAY Filmworks
ARRAY Filmworks is a film and television production company founded by filmmaker Ava DuVernay, known for championing diverse voices and inclusive storytelling.
- 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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13545808190a47544b0cc666e20 |
completed | April 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd22a194819089ae888e932566f1 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:26 p.m.