Triple
T20791149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candarid Beylik |
E511779
|
entity |
| Predicate | hasTerritory |
P285
|
FINISHED |
| Object | Kastamonu |
—
|
NE NERFINISHED |
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: Kastamonu | Statement: [Candarid Beylik, hasTerritory, Kastamonu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kastamonu Context triple: [Candarid Beylik, hasTerritory, Kastamonu]
-
A.
Kastamonu
chosen
Kastamonu is a historic city in northern Turkey known for its well-preserved Ottoman architecture and role as the administrative center of Kastamonu Province.
-
B.
Balıkesir
Balıkesir is a city in northwestern Turkey known for its agricultural economy, proximity to both the Marmara and Aegean seas, and role as the administrative center of Balıkesir Province.
-
C.
Zonguldak
Zonguldak is a port city on Turkey’s Black Sea coast known historically for its coal mining industry.
-
D.
Giresun
Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
-
E.
Afyon
Afyon is the former name of Afyonkarahisar, a city in western Turkey known for its strategic location, thermal springs, and opium poppy production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c29010508190bf2cf577d7f64754 |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:38 p.m.