Triple
T2796303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feridun Zaimoglu |
E53044
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Zaimoglu
Zaimoglu is the surname of Feridun Zaimoglu, a prominent German-Turkish author and artist known for his works on migration, identity, and multiculturalism.
|
E298692
|
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: Zaimoglu | Statement: [Feridun Zaimoglu, familyName, Zaimoglu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaimoglu Context triple: [Feridun Zaimoglu, familyName, Zaimoglu]
-
A.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
B.
Ersoy
Ersoy is a Turkish surname most notably borne by Mehmet Akif Ersoy, the poet of the Turkish National Anthem.
-
C.
Seyhun
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
-
D.
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.
-
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. 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: Zaimoglu Triple: [Feridun Zaimoglu, familyName, Zaimoglu]
Generated description
Zaimoglu is the surname of Feridun Zaimoglu, a prominent German-Turkish author and artist known for his works on migration, identity, and multiculturalism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zaimoglu Target entity description: Zaimoglu is the surname of Feridun Zaimoglu, a prominent German-Turkish author and artist known for his works on migration, identity, and multiculturalism.
-
A.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
B.
Ersoy
Ersoy is a Turkish surname most notably borne by Mehmet Akif Ersoy, the poet of the Turkish National Anthem.
-
C.
Seyhun
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
-
D.
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.
-
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. 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abddef754081908e6218dc2208e0fd |
completed | March 7, 2026, 8:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6646c2c81908157d8f03cb8376d |
completed | March 10, 2026, 7:21 a.m. |
| NEDg | Description generation | batch_69afc70a4e008190a846d23e1aa73bb1 |
completed | March 10, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc7907be88190b70458ed735261e8 |
completed | March 10, 2026, 7:26 a.m. |
Created at: March 6, 2026, 9:58 p.m.