Triple
T13893772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamil |
E334035
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Cemil |
E1050344
|
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: Cemil | Statement: [Jamil, hasVariant, Cemil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cemil Context triple: [Jamil, hasVariant, Cemil]
-
A.
Cemil
chosen
Cemil is a central fictional character from the Turkish novel and TV adaptation "Dudaktan Kalbe," known for his complex emotional struggles and romantic entanglements.
-
B.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
-
C.
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."
-
D.
Mehmet Ragif
Mehmet Ragif is the birth name of Mehmet Akif Ersoy, the renowned Turkish poet, writer, and author of the Turkish National Anthem.
-
E.
Tevfik
Tevfik is a central fictional character in the classic Turkish novel "Sinekli Bakkal" by Halide Edib Adıvar.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71ca8a881908ac02687fbfe62fb |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:15 p.m.