Triple
T21216506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şehzade Cihangir |
E522849
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cihangir |
—
|
NE NERFINISHED |
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: Cihangir | Statement: [Şehzade Cihangir, givenName, Cihangir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cihangir Context triple: [Şehzade Cihangir, givenName, Cihangir]
-
A.
Cihangir
chosen
Cihangir is a bohemian neighborhood in Istanbul known for its cafes, arts scene, and historic architecture, popular with artists, writers, and expatriates.
-
B.
Gürsu
Gürsu is a district and rapidly developing urban area located within Turkey’s northwestern Bursa Province.
-
C.
Turkomaneli
Turkomaneli is a term referring to the regions of Iraq predominantly inhabited by the Iraqi Turkmen ethnic minority.
-
D.
Sarıyahşi
Sarıyahşi is a small town and district in central Turkey known for its agricultural activities and rural character.
-
E.
Ceylanpınar
Ceylanpınar is a town and district in southeastern Turkey, located on the Syrian border and known for its large state-owned agricultural enterprises.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734744dcc81908b3065adc93b4b98 |
completed | April 21, 2026, 8:25 a.m. |
Created at: April 16, 2026, 3:41 p.m.