Triple
T6428492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Gemlik |
E128118
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Bursa |
E13331
|
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: Bursa | Statement: [Port of Gemlik, nearbyCity, Bursa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bursa Context triple: [Port of Gemlik, nearbyCity, Bursa]
-
A.
Bursa
chosen
Bursa is a major city in northwestern Turkey known historically as the first capital of the Ottoman Empire and today as an important industrial and cultural center.
-
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.
Samsun
Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
-
D.
Konya
Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
-
E.
Bilecik
Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06922a27881908c5571f2aa31e0c1 |
completed | March 22, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a5979208190b3bedb6234181245 |
completed | March 28, 2026, 12:01 a.m. |
Created at: March 22, 2026, 4:44 p.m.