Triple
T20580807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Başiskele |
E505647
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | İzmit Bay |
—
|
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 Bay | Statement: [Başiskele, locatedNear, İzmit Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İzmit Bay Context triple: [Başiskele, locatedNear, İzmit Bay]
-
A.
İzmit Bay
chosen
İzmit Bay is an inlet of the Sea of Marmara in northwestern Turkey, known as a major industrial and maritime area surrounded by several important cities.
-
B.
Port of İzmit
The Port of İzmit is a key Turkish maritime hub and industrial gateway located on the Gulf of İzmit along the Sea of Marmara.
-
C.
Namık
Namık is a Turkish masculine given name historically borne by notable figures such as the 19th-century writer and nationalist Namık Kemal.
-
D.
Demirköprü
Demirköprü is a neighborhood within the Karşıyaka district of İzmir, Turkey.
-
E.
Ayvacık
Ayvacık is a small town and district in Turkey’s Çanakkale Province, known for its traditional stone houses and proximity to the Aegean coast and ancient sites like Assos.
- 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a90e98a88190b5cb077973f97e68 |
completed | April 20, 2026, 10:30 p.m. |
Created at: April 16, 2026, 11:39 a.m.