Triple
T7303644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarık Akan |
E167919
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Yasemin Erkut
Yasemin Erkut is known as the spouse of the late Turkish actor and prominent cinema figure Tarık Akan.
|
E659226
|
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: Yasemin Erkut | Statement: [Tarık Akan, spouse, Yasemin Erkut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yasemin Erkut Context triple: [Tarık Akan, spouse, Yasemin Erkut]
-
A.
Nesrin Cansever
Nesrin Cansever is known as the wife of prominent Turkish modernist poet Edip Cansever.
-
B.
Canan Karatay
Canan Karatay is a Turkish cardiologist and academic known for her influential and often controversial views on nutrition and healthy living.
-
C.
Emine Hatun
Emine Hatun was an Ottoman consort known primarily as the wife of Sultan Mehmed I and the mother of Sultan Murad II.
-
D.
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.
-
E.
Şükran Güngör
Şükran Güngör was a prominent Turkish stage and film actor, celebrated for his work in modern Turkish theatre and his long association with the Kenter Theatre.
- 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: Yasemin Erkut Triple: [Tarık Akan, spouse, Yasemin Erkut]
Generated description
Yasemin Erkut is known as the spouse of the late Turkish actor and prominent cinema figure Tarık Akan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yasemin Erkut Target entity description: Yasemin Erkut is known as the spouse of the late Turkish actor and prominent cinema figure Tarık Akan.
-
A.
Nesrin Cansever
Nesrin Cansever is known as the wife of prominent Turkish modernist poet Edip Cansever.
-
B.
Canan Karatay
Canan Karatay is a Turkish cardiologist and academic known for her influential and often controversial views on nutrition and healthy living.
-
C.
Emine Hatun
Emine Hatun was an Ottoman consort known primarily as the wife of Sultan Mehmed I and the mother of Sultan Murad II.
-
D.
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.
-
E.
Şükran Güngör
Şükran Güngör was a prominent Turkish stage and film actor, celebrated for his work in modern Turkish theatre and his long association with the Kenter Theatre.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb352ec8190846eff044e08805e |
completed | March 27, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa7320bc819081e0b94e8909c4aa |
completed | March 28, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69c7fb1d9fdc8190943758de004057d6 |
completed | March 28, 2026, 4 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7fcc4dce881909262c5b67ddd980c |
completed | March 28, 2026, 4:07 p.m. |
Created at: March 27, 2026, 3:01 p.m.