Triple
T2149139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ural Mountains |
E47138
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Urals |
E47138
|
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: Urals | Statement: [Ural Mountains, alsoKnownAs, Urals]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Urals Context triple: [Ural Mountains, alsoKnownAs, Urals]
-
A.
Ural Mountains
chosen
The Ural Mountains are a long mountain range in western Russia that traditionally marks the natural boundary between Europe and Asia.
-
B.
Ural River
The Ural River is a major river in Russia and Kazakhstan that traditionally marks part of the boundary between the European and Asian continents.
-
C.
Ural region
The Ural region is a historical and geographical area of Russia centered around the Ural Mountains, traditionally seen as a boundary between Europe and Asia and known for its rich mineral resources and industrial centers.
-
D.
Caucasus
The Caucasus is a strategically vital mountainous region between the Black and Caspian Seas, historically contested by empires and known as a major crossroads of Europe and Asia.
-
E.
Ozyornaya
Ozyornaya is a Moscow Metro station on the Kalininsko–Solntsevskaya Line serving the western part of the city.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe44d2608190986467d43ee224d4 |
completed | March 7, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5d940bec8190998ef88ed44e5811 |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:44 p.m.