Triple
T14173337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L.I.E. |
E351266
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object |
Lot 47 Films
Lot 47 Films was an independent film distribution company known for releasing art-house and foreign films in the United States.
|
E1083533
|
NE FINISHED |
How this triple was built (4 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: Lot 47 Films | Statement: [L.I.E., distributor, Lot 47 Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lot 47 Films Context triple: [L.I.E., distributor, Lot 47 Films]
-
A.
Figment Films
Figment Films is a British film production company best known for producing the 2000 adventure drama film "The Beach."
-
B.
Figment Films
Figment Films is a film production company known for producing the 1997 romantic black comedy "A Life Less Ordinary," directed by Danny Boyle.
-
C.
Figment Films
Figment Films is a British film production company best known for producing the influential 1996 drama "Trainspotting."
-
D.
Shoebox Films
Shoebox Films is a British film production company known for producing independent and auteur-driven movies, including the 2019 thriller "Serenity."
-
E.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lot 47 Films Triple: [L.I.E., distributor, Lot 47 Films]
Generated description
Lot 47 Films was an independent film distribution company known for releasing art-house and foreign films in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lot 47 Films Target entity description: Lot 47 Films was an independent film distribution company known for releasing art-house and foreign films in the United States.
-
A.
Figment Films
Figment Films is a British film production company best known for producing the 2000 adventure drama film "The Beach."
-
B.
Figment Films
Figment Films is a film production company known for producing the 1997 romantic black comedy "A Life Less Ordinary," directed by Danny Boyle.
-
C.
Figment Films
Figment Films is a British film production company best known for producing the influential 1996 drama "Trainspotting."
-
D.
Shoebox Films
Shoebox Films is a British film production company known for producing independent and auteur-driven movies, including the 2019 thriller "Serenity."
-
E.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
- F. None of above. chosen
Provenance (5 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b5dcbc8190b0cfcce5e6c6d582 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf80a9b34819081c4ebf7429e875a |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd03511f048190a9f1eea0e37aef31 |
completed | May 7, 2026, 9:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd0406a770819082aeec43037f1243 |
completed | May 7, 2026, 9:28 p.m. |
Created at: April 10, 2026, 1:01 a.m.