Triple
T7429497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarıyer |
E171451
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Zekeriyaköy |
E662832
|
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: Zekeriyaköy | Statement: [Sarıyer, contains, Zekeriyaköy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zekeriyaköy Context triple: [Sarıyer, contains, Zekeriyaköy]
-
A.
Poyrazköy
Poyrazköy is a coastal neighborhood on the Asian side of Istanbul, Turkey, situated at the northern entrance of the Bosphorus Strait.
-
B.
Şirinköy
Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
-
C.
Bahçeköy
chosen
Bahçeköy is a neighborhood in Istanbul, Turkey, known for its proximity to the Belgrad Forest and several university campuses.
-
D.
Cihanbeyli
Cihanbeyli is a town and district in central Turkey known for its location on the Konya Plain and its agriculture-based local economy.
-
E.
Çerkezköy
Çerkezköy is an industrial and residential town in northwestern Turkey, located in Tekirdağ Province within the Thrace region.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3082f188190af5673d18ac7e87e |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827829a848190afca7b5f79c51c7c |
completed | March 28, 2026, 7:09 p.m. |
Created at: March 27, 2026, 3:12 p.m.