Triple
T10940870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunceli Province |
E258466
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Nazımiye |
E685887
|
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: Nazımiye | Statement: [Tunceli Province, hasDistrict, Nazımiye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nazımiye Context triple: [Tunceli Province, hasDistrict, Nazımiye]
-
A.
Nazımiye
chosen
Nazımiye is a small town and district in Tunceli Province in eastern Turkey, known as the birthplace of prominent Turkish politician Kemal Kılıçdaroğlu.
-
B.
Tevfikiye
Tevfikiye is a village in northwestern Turkey located close to the archaeological site of Hisarlik, widely identified with ancient Troy.
-
C.
Ülker
Ülker is a major Turkish food company best known for its wide range of confectionery and snack products.
-
D.
Gulussa
Gulussa was a 2nd-century BC Numidian prince and military leader, known as one of the sons of King Masinissa who played a role in the conflicts between Carthage and Rome.
-
E.
Bezmialem Kadın
Bezmialem Kadın was an influential consort of the Ottoman sultan, remembered for her political influence and extensive charitable works, including the founding of major hospitals and educational institutions.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c2821c8190a7b08276c4bfbf33 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23c0e940081908c84ea4cf3b877fc |
completed | April 17, 2026, 1:56 p.m. |
Created at: April 8, 2026, 9:23 p.m.