Triple
T7522835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahmet Necdet Sezer |
E177814
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ahmet |
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: Ahmet | Statement: [Ahmet Necdet Sezer, givenName, Ahmet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahmet Context triple: [Ahmet Necdet Sezer, givenName, Ahmet]
-
A.
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.
-
B.
Mehmet
Mehmet is a common Turkish male given name of Arabic origin, widely used across Turkey and among Turkish communities.
-
C.
Mahmut
Mahmut is a masculine given name commonly used in Turkish and related cultures, derived from the Arabic name Mahmoud.
-
D.
İsmet
İsmet is a Turkish given name most famously borne by İsmet İnönü, a prominent statesman and the second President of Turkey.
-
E.
Ismail Ankaravi
Ismail Ankaravi was an Ottoman-era Mevlevi scholar and Sufi commentator best known for his influential exegesis on Rumi’s Mathnawi.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c4f32081908b5162f4551adb6d |
completed | March 27, 2026, 9:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84efbbed48190baa687bb738a0c54 |
completed | March 28, 2026, 9:58 p.m. |
Created at: March 27, 2026, 3:46 p.m.