Triple
T7281800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İlhan Selçuk |
E163166
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | İlhan |
E393561
|
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: İlhan | Statement: [İlhan Selçuk, givenName, İlhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İlhan Context triple: [İlhan Selçuk, givenName, İlhan]
-
A.
İlhan
chosen
İlhan is a Turkish masculine given name commonly borne by notable figures in literature, arts, and public life.
-
B.
İlhan Selçuk
İlhan Selçuk was a prominent Turkish journalist, writer, and intellectual known for his influential columns and staunchly secular, Kemalist views.
-
C.
May Arslan
May Arslan was a Lebanese Druze aristocrat and political figure, best known as the wife of Druze leader Kamal Jumblatt and mother of politician Walid Jumblatt.
-
D.
Mahmut
Mahmut is a masculine given name commonly used in Turkish and related cultures, derived from the Arabic name Mahmoud.
-
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.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb4d3e3c8190a05cb5af5f52bd75 |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db379e1c81908ebd4c44504ce5fb |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:59 p.m.