Triple
T19362967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yıldız Park |
E484325
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ortaköy |
—
|
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: Ortaköy | Statement: [Yıldız Park, near, Ortaköy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ortaköy Context triple: [Yıldız Park, near, Ortaköy]
-
A.
Ortaköy
Ortaköy is a district and town in central Turkey’s Aksaray Province, known for its rural character and agricultural economy.
-
B.
Ortaköy
chosen
Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
-
C.
Çekmeköy
Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
-
D.
Kabataş
Kabataş is a coastal neighborhood in Istanbul, Turkey, known as a major transportation hub with ferry, tram, and funicular connections along the Bosphorus.
-
E.
Bayraklı
Bayraklı is a coastal district of İzmir, Turkey, known for its modern business centers, residential areas, and proximity to the city’s central urban core.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e619a897008190a2c62a50ca60de2d |
completed | April 20, 2026, 12:18 p.m. |
Created at: April 10, 2026, 1:34 p.m.