Triple
T22366652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 13 Minutes |
E552921
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Broth Film
Broth Film is a film production company known for producing the historical drama thriller "13 Minutes."
|
E1532310
|
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: Broth Film | Statement: [13 Minutes, productionCompany, Broth Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Broth Film Context triple: [13 Minutes, productionCompany, Broth Film]
-
A.
Film Begets Film
Film Begets Film is a critical study by film historian Jay Leyda that examines the influence of existing films on the creation and evolution of new cinematic works.
-
B.
The Bro
The Bro is a high-thrill water slide attraction at WhiteWater World, known for its fast, twisting ride experience.
-
C.
Thura Film
Thura Film is a Danish film production company known for producing the 1994 horror-thriller "Nightwatch."
-
D.
Robis Film
Robis Film is a film production company best known for producing the acclaimed Egyptian drama "The Night of Counting the Years."
-
E.
Chungeorahm Film
Chungeorahm Film is a South Korean film production company best known internationally for producing Bong Joon-ho’s monster movie "The Host."
- 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: Broth Film Triple: [13 Minutes, productionCompany, Broth Film]
Generated description
Broth Film is a film production company known for producing the historical drama thriller "13 Minutes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Broth Film Target entity description: Broth Film is a film production company known for producing the historical drama thriller "13 Minutes."
-
A.
Film Begets Film
Film Begets Film is a critical study by film historian Jay Leyda that examines the influence of existing films on the creation and evolution of new cinematic works.
-
B.
The Bro
The Bro is a high-thrill water slide attraction at WhiteWater World, known for its fast, twisting ride experience.
-
C.
Thura Film
Thura Film is a Danish film production company known for producing the 1994 horror-thriller "Nightwatch."
-
D.
Robis Film
Robis Film is a film production company best known for producing the acclaimed Egyptian drama "The Night of Counting the Years."
-
E.
Chungeorahm Film
Chungeorahm Film is a South Korean film production company best known internationally for producing Bong Joon-ho’s monster movie "The Host."
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580074dc819091305ac7017000d3 |
completed | April 29, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae065f01481909ddf2c27e2b471bf |
completed | May 18, 2026, 9:48 a.m. |
| NEDg | Description generation | batch_6a0ae16a8bcc8190852dd17f9c780123 |
completed | May 18, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ae1e16fac8190b0b56d00a87d173f |
completed | May 18, 2026, 9:54 a.m. |
Created at: April 16, 2026, 8:44 p.m.