Triple
T5491942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Turkey |
E123721
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Giresun |
E41325
|
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: Giresun | Statement: [Asian Turkey, containsCity, Giresun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giresun Context triple: [Asian Turkey, containsCity, Giresun]
-
A.
Kırklareli
Kırklareli is a city in northwestern Turkey known for its location near the Bulgarian border, agricultural economy, and historical Ottoman-era architecture.
-
B.
Trabzon
chosen
Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
-
C.
Denizli
Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
-
D.
Ardahan
Ardahan is a town in northeastern Turkey that serves as the capital of Ardahan Province near the border with Georgia.
-
E.
Isparta
Isparta is a city in southwestern Turkey known for its rose cultivation and production of rose oil and related products.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9280403c8190baaa3f7923449a37 |
completed | March 20, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf7fdc7cb08190b0e5b7321213f673 |
completed | March 22, 2026, 5:36 a.m. |
Created at: March 20, 2026, 2:10 p.m.