Triple
T2925672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahmet Ertegun |
E78836
|
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 Ertegun, givenName, Ahmet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahmet Context triple: [Ahmet Ertegun, 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.
Mustafa
Mustafa is the given birth name of Mustafa Kemal Atatürk, the founder and first president of the Republic of Turkey.
-
D.
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."
-
E.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97c086888190ba51ce659a6c4f50 |
completed | March 8, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0563a81788190b94fab34e41a76e7 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 8, 2026, 2:55 p.m.