Triple
T16707878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomsk Oblast |
E406019
|
entity |
| Predicate | hasPopulationCenter |
P2106
|
FINISHED |
| Object | Tomsk metropolitan area |
E208233
|
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: Tomsk metropolitan area | Statement: [Tomsk Oblast, hasPopulationCenter, Tomsk metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomsk metropolitan area Context triple: [Tomsk Oblast, hasPopulationCenter, Tomsk metropolitan area]
-
A.
Tomsk
chosen
Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
-
B.
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.
-
C.
Neftekamsk
Neftekamsk is an industrial city in the Republic of Bashkortostan, Russia, known for its oil-related industries and vehicle manufacturing.
-
D.
Kuznetsk
Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
-
E.
Arkhangelsk Urban Okrug
Arkhangelsk Urban Okrug is a municipal formation in Arkhangelsk Oblast, Russia, that encompasses the city of Arkhangelsk and its surrounding territories as a single urban administrative unit.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38337ecac8190bc4a9410ed7681ab |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b27fbce0819084852678798f264e |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:20 a.m.