Triple
T18502425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diriliş: Ertuğrul |
E452110
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Tekden Film
Tekden Film is a Turkish television and film production company best known internationally for producing the historical drama series "Diriliş: Ertuğrul."
|
E1328209
|
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: Tekden Film | Statement: [Diriliş: Ertuğrul, productionCompany, Tekden Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tekden Film Context triple: [Diriliş: Ertuğrul, productionCompany, Tekden Film]
-
A.
Teitler Film
Teitler Film is a film production company known for producing feature films such as the family sci-fi adventure "Zathura: A Space Adventure."
-
B.
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.
-
C.
Thura Film
Thura Film is a Danish film production company known for producing the 1994 horror-thriller "Nightwatch."
-
D.
Neue Constantin Film
Neue Constantin Film is a German film production and distribution company known for handling major domestic and international releases.
-
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: Tekden Film Triple: [Diriliş: Ertuğrul, productionCompany, Tekden Film]
Generated description
Tekden Film is a Turkish television and film production company best known internationally for producing the historical drama series "Diriliş: Ertuğrul."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tekden Film Target entity description: Tekden Film is a Turkish television and film production company best known internationally for producing the historical drama series "Diriliş: Ertuğrul."
-
A.
Teitler Film
Teitler Film is a film production company known for producing feature films such as the family sci-fi adventure "Zathura: A Space Adventure."
-
B.
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.
-
C.
Thura Film
Thura Film is a Danish film production company known for producing the 1994 horror-thriller "Nightwatch."
-
D.
Neue Constantin Film
Neue Constantin Film is a German film production and distribution company known for handling major domestic and international releases.
-
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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c535908190bdc90c58fc5bdaf7 |
completed | April 19, 2026, 7:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a047143903c8190979d96780689a068 |
completed | May 13, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a0486327b6c8190ac089fcc834582ff |
completed | May 13, 2026, 2:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0486d31e2c81908ca95db7baec64a0 |
completed | May 13, 2026, 2:12 p.m. |
Created at: April 10, 2026, 11:36 a.m.