Triple
T9318661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odintsovsky District |
E224188
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Gorki-2
Gorki-2 is a suburban settlement near Moscow, Russia, known as an affluent residential area within Odintsovsky District of Moscow Oblast.
|
E791819
|
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: Gorki-2 | Statement: [Odintsovsky District, contains, Gorki-2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorki-2 Context triple: [Odintsovsky District, contains, Gorki-2]
-
A.
Gorky Railway
Gorky Railway is a major regional railway network in Russia that operates routes across the Volga-Vyatka area, including services through Kazan.
-
B.
Stalinets
Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
-
C.
Shaposhnikov
Shaposhnikov is a Russian surname most notably associated with Soviet military leader Boris Shaposhnikov.
-
D.
Dynamo Kursk
Dynamo Kursk is a prominent Russian women's basketball club that competes in top domestic and European competitions, including the EuroLeague Women.
-
E.
Kirov Factory
Kirov Factory is a historic Russian heavy machinery and defense plant best known for producing Soviet tanks and other armored vehicles.
- 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: Gorki-2 Triple: [Odintsovsky District, contains, Gorki-2]
Generated description
Gorki-2 is a suburban settlement near Moscow, Russia, known as an affluent residential area within Odintsovsky District of Moscow Oblast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gorki-2 Target entity description: Gorki-2 is a suburban settlement near Moscow, Russia, known as an affluent residential area within Odintsovsky District of Moscow Oblast.
-
A.
Gorky Railway
Gorky Railway is a major regional railway network in Russia that operates routes across the Volga-Vyatka area, including services through Kazan.
-
B.
Stalinets
Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
-
C.
Shaposhnikov
Shaposhnikov is a Russian surname most notably associated with Soviet military leader Boris Shaposhnikov.
-
D.
Dynamo Kursk
Dynamo Kursk is a prominent Russian women's basketball club that competes in top domestic and European competitions, including the EuroLeague Women.
-
E.
Kirov Factory
Kirov Factory is a historic Russian heavy machinery and defense plant best known for producing Soviet tanks and other armored vehicles.
- 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd358b66148190a918c107490c8406 |
completed | April 1, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0c7c1fc848190bbb3ef6a1ed7a7d2 |
completed | April 4, 2026, 8:11 a.m. |
| NEDg | Description generation | batch_69d0ca049fdc819091e101d8cdcfb7e8 |
completed | April 4, 2026, 8:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0cc6239108190b921eface5cdd543 |
completed | April 4, 2026, 8:31 a.m. |
Created at: March 30, 2026, 7:38 p.m.