Triple
T7011350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filipp Oktyabrsky |
E162587
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Oktyabrsky
Oktyabrsky is a Russian surname most notably borne by Soviet Admiral Filipp Oktyabrsky, a prominent naval commander during World War II.
|
E634866
|
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: Oktyabrsky | Statement: [Filipp Oktyabrsky, familyName, Oktyabrsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oktyabrsky Context triple: [Filipp Oktyabrsky, familyName, Oktyabrsky]
-
A.
Oktyabrsk
Oktyabrsk is a small industrial city in Russia located on the Volga River within Samara Oblast.
-
B.
Oktyabrskaya
Oktyabrskaya is a Moscow Metro station known for its distinctive Soviet-era architecture and role as a key transfer point in the city’s subway network.
-
C.
Noyabrsk
Noyabrsk is a major oil and gas industry city in northern Russia, located in the Yamalo-Nenets region of Western Siberia.
-
D.
Mussau
Mussau is an island in Papua New Guinea’s Bismarck Archipelago, known for its distinct Oceanic languages and rich Melanesian-Polynesian cultural heritage.
-
E.
Vorontsovskaya
Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
- 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: Oktyabrsky Triple: [Filipp Oktyabrsky, familyName, Oktyabrsky]
Generated description
Oktyabrsky is a Russian surname most notably borne by Soviet Admiral Filipp Oktyabrsky, a prominent naval commander during World War II.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oktyabrsky Target entity description: Oktyabrsky is a Russian surname most notably borne by Soviet Admiral Filipp Oktyabrsky, a prominent naval commander during World War II.
-
A.
Oktyabrsk
Oktyabrsk is a small industrial city in Russia located on the Volga River within Samara Oblast.
-
B.
Oktyabrskaya
Oktyabrskaya is a Moscow Metro station known for its distinctive Soviet-era architecture and role as a key transfer point in the city’s subway network.
-
C.
Noyabrsk
Noyabrsk is a major oil and gas industry city in northern Russia, located in the Yamalo-Nenets region of Western Siberia.
-
D.
Mussau
Mussau is an island in Papua New Guinea’s Bismarck Archipelago, known for its distinct Oceanic languages and rich Melanesian-Polynesian cultural heritage.
-
E.
Vorontsovskaya
Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc5729448190af66dbd6f3e8936e |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a4bd424819097e1543ec59979ff |
completed | March 28, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69c76b1ef6f481908f4c4f610328f633 |
completed | March 28, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76c01679c8190b61f642c23c25ed5 |
completed | March 28, 2026, 5:49 a.m. |
Created at: March 27, 2026, 2:34 p.m.