Triple
T10170191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivano-Frankivsk Oblast |
E235309
|
entity |
| Predicate | containsMountain |
P10602
|
FINISHED |
| Object | Hoverla |
E86603
|
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: Hoverla | Statement: [Ivano-Frankivsk Oblast, containsMountain, Hoverla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoverla Context triple: [Ivano-Frankivsk Oblast, containsMountain, Hoverla]
-
A.
Hoverla
chosen
Hoverla is the tallest mountain in Ukraine, located in the Carpathian range and popular for hiking and tourism.
-
B.
Goryashchaya Sopka
Goryashchaya Sopka is an active stratovolcano located on Simushir Island in Russia’s Kuril Islands chain.
-
C.
Mount Narodnaya
Mount Narodnaya is a prominent peak in Russia known as the tallest mountain in the Ural range, marking the natural boundary between Europe and Asia.
-
D.
Dykh-Tau
Dykh-Tau is one of the highest and most prominent mountains in the Caucasus range, located on the border of Russia and Georgia.
-
E.
Kopet Dagh
Kopet Dagh is a mountain range in Central Asia forming part of the natural border between Turkmenistan and Iran.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9d36608190be78665cc3410cf2 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300f7aafc8190be874efc755bd188 |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:10 p.m.