Triple
T13814909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heartland |
E331987
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
SEVEN24 Films
SEVEN24 Films is a Canadian television and film production company best known for producing the long-running family drama series "Heartland."
|
E1064294
|
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: SEVEN24 Films | Statement: [Heartland, productionCompany, SEVEN24 Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEVEN24 Films Context triple: [Heartland, productionCompany, SEVEN24 Films]
-
A.
Crown Seven Films
Crown Seven Films was a Philippine film production company that later became known as GMA Films, the movie arm of the GMA Network.
-
B.
Diaphana Films
Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
-
C.
Beyond Films
Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
E.
SEPT Films
SEPT Films is a French film distribution company known for releasing independent and auteur-driven cinema.
- 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: SEVEN24 Films Triple: [Heartland, productionCompany, SEVEN24 Films]
Generated description
SEVEN24 Films is a Canadian television and film production company best known for producing the long-running family drama series "Heartland."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SEVEN24 Films Target entity description: SEVEN24 Films is a Canadian television and film production company best known for producing the long-running family drama series "Heartland."
-
A.
Crown Seven Films
Crown Seven Films was a Philippine film production company that later became known as GMA Films, the movie arm of the GMA Network.
-
B.
Diaphana Films
Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
-
C.
Beyond Films
Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
E.
SEPT Films
SEPT Films is a French film distribution company known for releasing independent and auteur-driven cinema.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8e0112481909deb31f8614f8b93 |
completed | May 3, 2026, 9:06 p.m. |
| NEDg | Description generation | batch_69f7b9d773f881908660e8a0645d318d |
completed | May 3, 2026, 9:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7bbf47c888190be32a4105903120a |
completed | May 3, 2026, 9:19 p.m. |
Created at: April 9, 2026, 10:12 p.m.