Triple
T17265726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Обь |
E419121
|
entity |
| Predicate | имеетГородНаБерегу |
P969
|
FINISHED |
| Object | Барнаул |
E208234
|
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: Барнаул | Statement: [Обь, имеетГородНаБерегу, Барнаул]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Барнаул Context triple: [Обь, имеетГородНаБерегу, Барнаул]
-
A.
Barnaul
chosen
Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
-
B.
Krasnoyarsk
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.
-
C.
Novokuznetsk
Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
-
D.
Severobaikalsk
Severobaikalsk is a small town in northern Buryatia, Russia, located on the northern shore of Lake Baikal and serving as an important transport hub in eastern Siberia.
-
E.
Sayanogorsk
Sayanogorsk is a town in the Republic of Khakassia, Russia, known as an industrial center in southern Siberia and a hub for aluminum production.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f44ec7c81909a925fc8692b0a6c |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c3ca3f08190b7da411a5638214e |
completed | May 11, 2026, 7:58 a.m. |
Created at: April 10, 2026, 5:40 a.m.