Triple
T2908855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Vitsi |
E63632
|
entity |
| Predicate | hasRoadAccessFrom |
P22549
|
FINISHED |
| Object | Kastoria |
E136980
|
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: Kastoria | Statement: [Mount Vitsi, hasRoadAccessFrom, Kastoria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kastoria Context triple: [Mount Vitsi, hasRoadAccessFrom, Kastoria]
-
A.
Kastoria
chosen
Kastoria is a picturesque lakeside city in northern Greece renowned for its Byzantine churches, traditional stone mansions, and historic fur trade.
-
B.
Votkinsk
Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
-
C.
Odintsovo
Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
-
D.
Alchevsk
Alchevsk is an industrial city in eastern Ukraine known for its steel and metallurgical plants.
-
E.
Tselinograd
Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0d329c88190b6fcaef0be1799eb |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b334049c5c8190b870e790795cbec4 |
completed | March 12, 2026, 9:45 p.m. |
Created at: March 6, 2026, 10:11 p.m.