Triple
T16781456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rundown |
E407865
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Misher Films |
E257912
|
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: Misher Films | Statement: [The Rundown, productionCompany, Misher Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Misher Films Context triple: [The Rundown, productionCompany, Misher Films]
-
A.
Misher Films
chosen
Misher Films is an American film production company known for producing a range of mainstream Hollywood movies, including the biographical sports comedy-drama "Fighting with My Family."
-
B.
Muktha Films
Muktha Films is an Indian film production company best known for producing acclaimed Tamil cinema, including the classic crime drama "Nayakan."
-
C.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
D.
Nala Films
Nala Films is an independent film production company known for financing and producing critically acclaimed feature films.
-
E.
Sahai Films
Sahai Films is an Indian film production company known for producing the cult classic television film "In Which Annie Gives It Those Ones."
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b216726881908ddc9cdc772cd5e4 |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b287a96c8190a16d7c76d05be106 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:22 a.m.