Triple
T12361934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Termal |
E294760
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Yalova city |
E60878
|
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: Yalova city | Statement: [Termal, locatedNear, Yalova city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yalova city Context triple: [Termal, locatedNear, Yalova city]
-
A.
Yalova
chosen
Yalova is a small coastal city in northwestern Turkey, known for its thermal springs, seaside promenade, and proximity to Istanbul across the Sea of Marmara.
-
B.
Florya
Florya is a coastal neighborhood in Istanbul, Turkey, known for its residential areas, seaside promenade, and recreational facilities.
-
C.
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.
-
D.
Beykoz
Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
-
E.
İnegöl
İnegöl is a town and district in northwestern Turkey known for its furniture industry and distinctive İnegöl köfte (meatballs).
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f91a1908190a8a4fa9da3b47933 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b90779881909893d1e6877ce567 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:54 p.m.