Triple
T21233014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muhteşem Yüzyıl |
E523271
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object |
Yağmur Taylan
Yağmur Taylan is a Turkish film and television director best known as one half of the Taylan Brothers duo behind several acclaimed series and films.
|
E1473858
|
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: Yağmur Taylan | Statement: [Muhteşem Yüzyıl, director, Yağmur Taylan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yağmur Taylan Context triple: [Muhteşem Yüzyıl, director, Yağmur Taylan]
-
A.
Burak Deniz
Burak Deniz is a Turkish actor best known for his leading roles in popular television dramas and romantic series.
-
B.
Emin Özmen
Emin Özmen is a Turkish photojournalist renowned for his powerful documentation of conflict, human rights abuses, and humanitarian crises.
-
C.
Melih Gökçek
Melih Gökçek is a Turkish politician best known for his long tenure as the mayor of Ankara and his prominent role in conservative Islamist politics.
-
D.
Burak Özçivit
Burak Özçivit is a Turkish actor and former model best known for his leading roles in popular Turkish television dramas and films.
-
E.
Serdar Gökhan
Serdar Gökhan is a veteran Turkish actor known for his roles in historical dramas and classic Yeşilçam-era films.
- 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: Yağmur Taylan Triple: [Muhteşem Yüzyıl, director, Yağmur Taylan]
Generated description
Yağmur Taylan is a Turkish film and television director best known as one half of the Taylan Brothers duo behind several acclaimed series and films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yağmur Taylan Target entity description: Yağmur Taylan is a Turkish film and television director best known as one half of the Taylan Brothers duo behind several acclaimed series and films.
-
A.
Burak Deniz
Burak Deniz is a Turkish actor best known for his leading roles in popular television dramas and romantic series.
-
B.
Emin Özmen
Emin Özmen is a Turkish photojournalist renowned for his powerful documentation of conflict, human rights abuses, and humanitarian crises.
-
C.
Melih Gökçek
Melih Gökçek is a Turkish politician best known for his long tenure as the mayor of Ankara and his prominent role in conservative Islamist politics.
-
D.
Burak Özçivit
Burak Özçivit is a Turkish actor and former model best known for his leading roles in popular Turkish television dramas and films.
-
E.
Serdar Gökhan
Serdar Gökhan is a veteran Turkish actor known for his roles in historical dramas and classic Yeşilçam-era films.
- 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734b1524c8190a77eaf2fabd601c3 |
completed | April 21, 2026, 8:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0986edbed88190885fc8cb47b9739a |
completed | May 17, 2026, 9:14 a.m. |
| NEDg | Description generation | batch_6a098915325c8190bb956070b2714c95 |
completed | May 17, 2026, 9:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a098a24f1948190aada13777f829700 |
completed | May 17, 2026, 9:28 a.m. |
Created at: April 16, 2026, 3:45 p.m.