Triple
T15008712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lovebirds |
E377778
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
MRC Film
MRC Film is an American film and television production company known for backing a range of high-profile, commercially successful and critically acclaimed projects.
|
E1132190
|
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: MRC Film | Statement: [The Lovebirds, productionCompany, MRC Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRC Film Context triple: [The Lovebirds, productionCompany, MRC Film]
-
A.
Mavin Films
Mavin Films is the film and visual content production arm associated with Nigerian music label Mavin Records.
-
B.
MPC Film
MPC Film is a major visual effects and animation studio known for creating high-end CGI and VFX for blockbuster films and television.
-
C.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
D.
MLR Films
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
-
E.
Clerkenwell Films
Clerkenwell Films is a British television and film production company known for creating acclaimed dramas and comedies such as "Misfits" and "Lovesick."
- 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: MRC Film Triple: [The Lovebirds, productionCompany, MRC Film]
Generated description
MRC Film is an American film and television production company known for backing a range of high-profile, commercially successful and critically acclaimed projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MRC Film Target entity description: MRC Film is an American film and television production company known for backing a range of high-profile, commercially successful and critically acclaimed projects.
-
A.
Mavin Films
Mavin Films is the film and visual content production arm associated with Nigerian music label Mavin Records.
-
B.
MPC Film
MPC Film is a major visual effects and animation studio known for creating high-end CGI and VFX for blockbuster films and television.
-
C.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
D.
MLR Films
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
-
E.
Clerkenwell Films
Clerkenwell Films is a British television and film production company known for creating acclaimed dramas and comedies such as "Misfits" and "Lovesick."
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe96a52bb08190961e3f18d751fe2a |
completed | May 9, 2026, 2:06 a.m. |
| NEDg | Description generation | batch_69fe98bf505c819089740180a763db34 |
completed | May 9, 2026, 2:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9aab47888190812ff9732380e124 |
completed | May 9, 2026, 2:23 a.m. |
Created at: April 10, 2026, 2:55 a.m.