Triple
T21233044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muhteşem Yüzyıl |
E523271
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Okan Yalabık
Okan Yalabık is a Turkish actor known for his prominent roles in television series, films, and theater.
|
E1473863
|
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: Okan Yalabık | Statement: [Muhteşem Yüzyıl, hasCastMember, Okan Yalabık]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okan Yalabık Context triple: [Muhteşem Yüzyıl, hasCastMember, Okan Yalabık]
-
A.
Dursunbey
Dursunbey is a town and district in western Turkey known for its forestry, timber production, and rural character within Balıkesir Province.
-
B.
Gündoğmuş
Gündoğmuş is a small inland district and town in Turkey known for its mountainous terrain and location within Antalya Province in the Mediterranean region.
-
C.
Göksun
Göksun is a town and district in southern Turkey known for its mountainous terrain and location within Kahramanmaraş Province.
-
D.
Bamsi Beyrek
Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
-
E.
Gündoğdu
Gündoğdu is a small settlement located on Marmara Island in northwestern Turkey.
- 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: Okan Yalabık Triple: [Muhteşem Yüzyıl, hasCastMember, Okan Yalabık]
Generated description
Okan Yalabık is a Turkish actor known for his prominent roles in television series, films, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Okan Yalabık Target entity description: Okan Yalabık is a Turkish actor known for his prominent roles in television series, films, and theater.
-
A.
Dursunbey
Dursunbey is a town and district in western Turkey known for its forestry, timber production, and rural character within Balıkesir Province.
-
B.
Gündoğmuş
Gündoğmuş is a small inland district and town in Turkey known for its mountainous terrain and location within Antalya Province in the Mediterranean region.
-
C.
Göksun
Göksun is a town and district in southern Turkey known for its mountainous terrain and location within Kahramanmaraş Province.
-
D.
Bamsi Beyrek
Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
-
E.
Gündoğdu
Gündoğdu is a small settlement located on Marmara Island in northwestern Turkey.
- 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.