Triple
T17083771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tevfik Fikret |
E414540
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fikret |
E414540
|
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: Fikret | Statement: [Tevfik Fikret, familyName, Fikret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fikret Context triple: [Tevfik Fikret, familyName, Fikret]
-
A.
Fikret
chosen
Fikret is a Turkish surname most notably associated with the influential poet and educator Tevfik Fikret, a leading figure in late Ottoman literature.
-
B.
Wasfi
Wasfi is an Arabic masculine given name commonly used in the Middle East.
-
C.
Faruk
Faruk is a central character in Orhan Pamuk’s novel "Silent House," representing one of the intertwined perspectives that explore family tensions and Turkey’s social and political transformations.
-
D.
Ziya
Ziya is a masculine given name of Turkish origin, historically associated with notable figures such as sociologist and nationalist thinker Ziya Gökalp.
-
E.
Fayiz
Fayiz is a masculine given name of Arabic origin, commonly used as a variant transliteration of the name Fayez.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe4d3908190b23ce3c2d3fe7d14 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ee416c4819087e7ae0ead47867a |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:35 a.m.