Triple
T9815464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakarya Province |
E238390
|
entity |
| Predicate | closeToCity |
P36605
|
FINISHED |
| Object | Izmit |
E654719
|
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: Izmit | Statement: [Sakarya Province, closeToCity, Izmit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Izmit Context triple: [Sakarya Province, closeToCity, Izmit]
-
A.
Izmit
chosen
Izmit is an industrial and port city in northwestern Turkey, located east of Istanbul along the Gulf of Izmit.
-
B.
Giresun
Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
-
C.
Ardahan
Ardahan is a town in northeastern Turkey that serves as the capital of Ardahan Province near the border with Georgia.
-
D.
Isparta
Isparta is a city in southwestern Turkey known for its rose cultivation and production of rose oil and related products.
-
E.
Darıca
Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc6c64dc8190979be34255dc22e5 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:30 p.m.