Triple
T17124250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jemal Pasha |
E415549
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cemal |
E1096899
|
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: Cemal | Statement: [Jemal Pasha, givenName, Cemal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cemal Context triple: [Jemal Pasha, givenName, Cemal]
-
A.
Cemal
chosen
Cemal is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
-
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.
Tevfik
Tevfik is a central fictional character in the classic Turkish novel "Sinekli Bakkal" by Halide Edib Adıvar.
-
D.
Cemil
Cemil is a central fictional character from the Turkish novel and TV adaptation "Dudaktan Kalbe," known for his complex emotional struggles and romantic entanglements.
-
E.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f025fce481908e261f2e363e14f9 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a016741fe6c81908ebbb022749915ab |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:36 a.m.