Triple
T11623703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bursa Province |
E276205
|
entity |
| Predicate | hasMajorPort |
P942
|
FINISHED |
| Object | Mudanya |
E565224
|
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: Mudanya | Statement: [Bursa Province, hasMajorPort, Mudanya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mudanya Context triple: [Bursa Province, hasMajorPort, Mudanya]
-
A.
Mudanya
chosen
Mudanya is a coastal town and district in Bursa Province, northwestern Turkey, situated along the Sea of Marmara and known for its port, historic architecture, and role in the Turkish War of Independence.
-
B.
Nimule
Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
-
C.
Tontemboan
Tontemboan is an Austronesian language spoken by the Tontemboan people in North Sulawesi, Indonesia.
-
D.
Abong-Mbang
Abong-Mbang is a town in eastern Cameroon that serves as a local administrative and commercial center in the East Region.
-
E.
Kalungu
Kalungu is a district in central Uganda that forms part of the traditional Buganda Kingdom 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a122a3708190ab6513dad4c4fde7 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef13491c0c819085f4ea17ad74612a |
completed | April 27, 2026, 7:42 a.m. |
Created at: April 8, 2026, 9:39 p.m.