Triple
T13932905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How High |
E335035
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Jersey Films |
E344147
|
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: Jersey Films | Statement: [How High, productionCompany, Jersey Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jersey Films Context triple: [How High, productionCompany, Jersey Films]
-
A.
Jersey Films
chosen
Jersey Films is an American film production company best known for producing influential independent and cult-classic movies in the 1990s and 2000s.
-
B.
Jersey Films 2nd Avenue
Jersey Films 2nd Avenue is a film and television production company known for developing and producing a range of feature films and media projects.
-
C.
Ecosse Films
Ecosse Films is a British film and television production company known for producing period dramas and independent feature films.
-
D.
Fountainbridge Films
Fountainbridge Films is a film production company co-founded by actor Sean Connery, known for producing movies such as the thriller "Entrapment."
-
E.
Celandine Films
Celandine Films is a film production company best known for producing the British comedy film "Monty Python’s The Meaning of Life."
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf28df081908d897d7b9ec7939d |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce865ab4819088221189344b3801 |
completed | May 3, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.