Triple
T16294110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomris Uyar |
E395601
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Ülkü Tamer |
E1196625
|
NE FINISHED |
How this triple was built (2 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: Ülkü Tamer | Statement: [Tomris Uyar, spouse, Ülkü Tamer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ülkü Tamer Context triple: [Tomris Uyar, spouse, Ülkü Tamer]
-
A.
Ülkü Tamer
chosen
Ülkü Tamer was a prominent Turkish poet, translator, and journalist associated with the İkinci Yeni (Second New) movement in modern Turkish literature.
-
B.
Sadi Irmak
Sadi Irmak was a Turkish physician, academic, and politician who briefly served as Prime Minister of Turkey in the mid-1970s.
-
C.
Kan Turali
Kan Turali is a heroic warrior figure from the Turkic epic tradition, celebrated for his bravery and central role in the Dede Korkut stories.
-
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.
Serdar
Serdar is a town in western Turkmenistan that serves as an administrative and transport hub in the Balkan Region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2c255881909d99c43770475329 |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9965b8819080278ccef15288aa |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:05 a.m.