Triple
T7429507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarıyer |
E171451
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Şişli |
E630599
|
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: Şişli | Statement: [Sarıyer, borderedBy, Şişli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Şişli Context triple: [Sarıyer, borderedBy, Şişli]
-
A.
Üsküdar
Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
-
B.
Şişli district
chosen
Şişli district is a central and densely populated area on Istanbul’s European side, known for its commercial centers, business districts, and historic neighborhoods.
-
C.
Ümraniye
Ümraniye is a densely populated residential and commercial district located on the Asian side of Istanbul, Turkey.
-
D.
Kadıköy
Kadıköy is a historic district on the Asian side of Istanbul, Turkey, known for its ancient roots (including the site of the Council of Chalcedon), vibrant cultural life, and bustling waterfront.
-
E.
Sarıyer
Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
- 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_69c9567fd22881909bd8f4972144be22 |
completed | March 29, 2026, 4:42 p.m. |
Created at: March 27, 2026, 3:12 p.m.