Triple
T13229618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fevzi Çakmak |
E314976
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Fevzi
Fevzi is a Turkish masculine given name, historically borne by notable figures such as military leader and statesman Fevzi Çakmak.
|
E1029976
|
NE FINISHED |
How this triple was built (4 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: Fevzi | Statement: [Fevzi Çakmak, givenName, Fevzi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fevzi Context triple: [Fevzi Çakmak, givenName, Fevzi]
-
A.
Fuat
Fuat is a Turkish masculine given name commonly borne by notable figures in politics, academia, and the arts.
-
B.
Serdar
Serdar is a town in western Turkmenistan that serves as an administrative and transport hub in the Balkan Region.
-
C.
Gaziosmanpaşa
Gaziosmanpaşa is a densely populated residential and commercial district on the European side of Istanbul, known for its rapid urbanization and diverse working- and middle-class communities.
-
D.
Halil
Halil is the given name of Çandarlı Halil Pasha, a prominent Ottoman statesman and grand vizier in the 15th century.
-
E.
Ziya
Ziya is a masculine given name of Turkish origin, historically associated with notable figures such as sociologist and nationalist thinker Ziya Gökalp.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Fevzi Triple: [Fevzi Çakmak, givenName, Fevzi]
Generated description
Fevzi is a Turkish masculine given name, historically borne by notable figures such as military leader and statesman Fevzi Çakmak.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fevzi Target entity description: Fevzi is a Turkish masculine given name, historically borne by notable figures such as military leader and statesman Fevzi Çakmak.
-
A.
Fuat
Fuat is a Turkish masculine given name commonly borne by notable figures in politics, academia, and the arts.
-
B.
Serdar
Serdar is a town in western Turkmenistan that serves as an administrative and transport hub in the Balkan Region.
-
C.
Gaziosmanpaşa
Gaziosmanpaşa is a densely populated residential and commercial district on the European side of Istanbul, known for its rapid urbanization and diverse working- and middle-class communities.
-
D.
Halil
Halil is the given name of Çandarlı Halil Pasha, a prominent Ottoman statesman and grand vizier in the 15th century.
-
E.
Ziya
Ziya is a masculine given name of Turkish origin, historically associated with notable figures such as sociologist and nationalist thinker Ziya Gökalp.
- F. None of above. chosen
Provenance (5 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d336ae08190bfc118cfbefddf84 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a35ccc88190881a7066b7af8fea |
completed | May 3, 2026, 8:41 a.m. |
| NEDg | Description generation | batch_69f70c000da081909297f3d24666b6a5 |
completed | May 3, 2026, 8:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70ce60a7081908f9498fcfec98e90 |
completed | May 3, 2026, 8:52 a.m. |
Created at: April 9, 2026, 9:21 p.m.