Triple
T2886611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yenisei River |
E59520
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Krasnoyarsk (city) |
E199248
|
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: Krasnoyarsk (city) | Statement: [Yenisei River, passesThrough, Krasnoyarsk (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krasnoyarsk (city) Context triple: [Yenisei River, passesThrough, Krasnoyarsk (city)]
-
A.
Krasnoyarsk
chosen
Krasnoyarsk is a large industrial and cultural city in central Russia, situated on the Yenisei River and known as one of the key urban centers of Siberia.
-
B.
Krasnoyarsk, Russia
Krasnoyarsk is a major industrial and cultural city in central Siberia, Russia, situated on the Yenisei River and known as a key hub of the region.
-
C.
Barnaul
Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
-
D.
Omsk
Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
-
E.
Novokuznetskaya
Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe0463ccc8190bf08330f40d0cfdc |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c5602f081908dba5df679ca9733 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 6, 2026, 10:03 p.m.