Triple
T12028110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Uzhin |
E286330
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Valday |
E781405
|
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: Valday | Statement: [Mount Uzhin, nearbyCity, Valday]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valday Context triple: [Mount Uzhin, nearbyCity, Valday]
-
A.
Valday
chosen
Valday is a historic town in Russia’s Novgorod Oblast, known for its scenic lakes and location along major transport routes between Moscow and St. Petersburg.
-
B.
Vytegra
Vytegra is a small town in northwestern Russia known as a regional center near Lake Onega and the White Sea–Baltic Canal.
-
C.
Thalheim
Thalheim is a town in the German state of Saxony-Anhalt that was incorporated into the larger city of Bitterfeld-Wolfen.
-
D.
Mulgimaa
Mulgimaa is a historic cultural region in southern Estonia known for its distinct Mulgi dialect, traditional folk culture, and influential role in Estonian national awakening.
-
E.
Liausson
Liausson is a small commune in southern France’s Hérault department, known for its scenic setting on the shores of the artificial Lac du Salagou.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903f13ae8819097a5740f7c51df82 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b8111b88190a42a8904a2d26862 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 8, 2026, 9:47 p.m.