Triple
T2581747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samara River |
E57106
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object |
Novokuybyshevsk
Novokuybyshevsk is an industrial city in Samara Oblast, Russia, known for its major oil refining and petrochemical industries.
|
E386558
|
NE FINISHED |
How this triple was built (4 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: Novokuybyshevsk | Statement: [Samara River, hasCityOnRiver, Novokuybyshevsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Novokuybyshevsk Context triple: [Samara River, hasCityOnRiver, Novokuybyshevsk]
-
A.
Kirovsk
Kirovsk is an industrial town in Russia’s Murmansk Oblast, known for its mining industry and location in the Khibiny Mountains on the Kola Peninsula.
-
B.
Kirovsk
Kirovsk is a small industrial town in northwestern Russia, situated near Saint Petersburg along the Neva River.
-
C.
Novokuznetskaya
Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
-
D.
Novocherkassk
Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Novokuybyshevsk Triple: [Samara River, hasCityOnRiver, Novokuybyshevsk]
Generated description
Novokuybyshevsk is an industrial city in Samara Oblast, Russia, known for its major oil refining and petrochemical industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Novokuybyshevsk Target entity description: Novokuybyshevsk is an industrial city in Samara Oblast, Russia, known for its major oil refining and petrochemical industries.
-
A.
Kirovsk
Kirovsk is a small industrial town in northwestern Russia, situated near Saint Petersburg along the Neva River.
-
B.
Kirovsk
Kirovsk is an industrial town in Russia’s Murmansk Oblast, known for its mining industry and location in the Khibiny Mountains on the Kola Peninsula.
-
C.
Novokuznetskaya
Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
-
D.
Novocherkassk
Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
-
E.
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.
- F. None of above. chosen
Provenance (5 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c843bc8190837cea3441bf3ca1 |
completed | March 7, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e4c13494819095821f44916329c9 |
completed | March 14, 2026, 4:32 a.m. |
| NEDg | Description generation | batch_69b4e88d88248190a4061327296818c7 |
completed | March 14, 2026, 4:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e8f38ba88190944236b2e8ae743e |
completed | March 14, 2026, 4:49 a.m. |
Created at: March 6, 2026, 9:49 p.m.