Triple
T20537199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kocaeli Metropolitan Municipality |
E504231
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | İzmit |
—
|
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: İzmit | Statement: [Kocaeli Metropolitan Municipality, seat, İzmit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İzmit Context triple: [Kocaeli Metropolitan Municipality, seat, İzmit]
-
A.
İzmit
chosen
İzmit is a city in northwestern Turkey on the Gulf of İzmit, historically significant as the site of ancient Nicomedia and an important industrial and transportation hub near Istanbul.
-
B.
Eskişehir
Eskişehir is a major university and industrial city in northwestern Turkey, known for its vibrant student life, modern urban design, and rich cultural heritage.
-
C.
Adapazarı
Adapazarı is a city in northwestern Turkey that serves as the administrative center of Sakarya Province and is known for its agricultural production and regional commerce.
-
D.
Izmir
Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
-
E.
Samsun
Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a28f2f1081908f656d790ff182ff |
completed | April 20, 2026, 10:02 p.m. |
Created at: April 16, 2026, 11:37 a.m.