Triple
T22433351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | What Will People Say |
E554551
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Mer Film
Mer Film is a Norwegian film production company known for producing critically acclaimed, socially engaged feature films and documentaries.
|
E1536444
|
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: Mer Film | Statement: [What Will People Say, productionCompany, Mer Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mer Film Context triple: [What Will People Say, productionCompany, Mer Film]
-
A.
Lea Film
Lea Film was an Italian film production company active during the mid-20th century, known for contributing to genre cinema including giallo and thriller films.
-
B.
Mantaray Film
Mantaray Film is a Swedish film production company known for producing acclaimed documentaries and feature films, often with a strong focus on personal and artistic stories.
-
C.
Cre Film
Cre Film is a film production company known for helping produce the critically acclaimed drama "The Florida Project."
-
D.
Tekden Film
Tekden Film is a Turkish television and film production company best known internationally for producing the historical drama series "Diriliş: Ertuğrul."
-
E.
Geria Film
Geria Film is a film production company known for producing the movie "Fedora."
- 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: Mer Film Triple: [What Will People Say, productionCompany, Mer Film]
Generated description
Mer Film is a Norwegian film production company known for producing critically acclaimed, socially engaged feature films and documentaries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mer Film Target entity description: Mer Film is a Norwegian film production company known for producing critically acclaimed, socially engaged feature films and documentaries.
-
A.
Lea Film
Lea Film was an Italian film production company active during the mid-20th century, known for contributing to genre cinema including giallo and thriller films.
-
B.
Mantaray Film
Mantaray Film is a Swedish film production company known for producing acclaimed documentaries and feature films, often with a strong focus on personal and artistic stories.
-
C.
Cre Film
Cre Film is a film production company known for helping produce the critically acclaimed drama "The Florida Project."
-
D.
Tekden Film
Tekden Film is a Turkish television and film production company best known internationally for producing the historical drama series "Diriliş: Ertuğrul."
-
E.
Geria Film
Geria Film is a film production company known for producing the movie "Fedora."
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a3320448190ae3931062599116e |
completed | April 29, 2026, 1:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0af0f90f5881908f0011690cb0f1e4 |
completed | May 18, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_6a0af268db2881908706641ad1e41f79 |
completed | May 18, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b08e411048190a368214c57c35d5e |
completed | May 18, 2026, 12:41 p.m. |
Created at: April 16, 2026, 8:47 p.m.