Triple
T7043394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ekrem İmamoğlu |
E163570
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ekrem |
E147433
|
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: Ekrem | Statement: [Ekrem İmamoğlu, givenName, Ekrem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ekrem Context triple: [Ekrem İmamoğlu, givenName, Ekrem]
-
A.
Kerim Bey
Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
-
B.
Güntekin
Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
-
C.
Ahmet
chosen
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
-
D.
Emre
Emre is a Turkish surname and given name most notably associated with Yunus Emre, a revered 13th–14th century Sufi poet and mystic.
-
E.
Selim Işık
Selim Işık is a central, tragicomic character in Oğuz Atay’s novel "Tutunamayanlar," symbolizing the alienated intellectual who cannot adapt to modern Turkish society.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e235a2e08190bb049ee6e719f0f9 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7887141ac81909cb5e996a89e4ec5 |
completed | March 28, 2026, 7:51 a.m. |
Created at: March 27, 2026, 2:36 p.m.