Triple
T2438408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kama River |
E53216
|
entity |
| Predicate | majorCityOnRiver |
P316
|
FINISHED |
| Object |
Sarapul
Sarapul is a historic city in Russia’s Udmurt Republic, known as a regional industrial and transport center on the eastern edge of European Russia.
|
E314407
|
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: Sarapul | Statement: [Kama River, majorCityOnRiver, Sarapul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarapul Context triple: [Kama River, majorCityOnRiver, Sarapul]
-
A.
Skovorodino
Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
-
B.
Otradnoye
Otradnoye is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Otradnoye District in northern Moscow.
-
C.
Kastornoye
Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
-
D.
Karachayevsk
Karachayevsk is a town in southwestern Russia located in the North Caucasus region, serving as one of the main urban centers of the Karachay-Cherkess Republic.
-
E.
Yuryev
Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
- 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: Sarapul Triple: [Kama River, majorCityOnRiver, Sarapul]
Generated description
Sarapul is a historic city in Russia’s Udmurt Republic, known as a regional industrial and transport center on the eastern edge of European Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarapul Target entity description: Sarapul is a historic city in Russia’s Udmurt Republic, known as a regional industrial and transport center on the eastern edge of European Russia.
-
A.
Skovorodino
Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
-
B.
Otradnoye
Otradnoye is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Otradnoye District in northern Moscow.
-
C.
Kastornoye
Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
-
D.
Karachayevsk
Karachayevsk is a town in southwestern Russia located in the North Caucasus region, serving as one of the main urban centers of the Karachay-Cherkess Republic.
-
E.
Yuryev
Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f4d2dc8190b3c264a6c20d1bd5 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc308f388190a10f79a02a867057 |
completed | March 11, 2026, 5:22 a.m. |
| NEDg | Description generation | batch_69b0fd07b82881908d52ab2db2f2e54c |
completed | March 11, 2026, 5:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0fdba0fd88190a2e760f1770e846c |
completed | March 11, 2026, 5:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.