Triple
T9318669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odintsovsky District |
E224188
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kubinka
Kubinka is a town in Moscow Oblast, Russia, best known for its large military airbase and the renowned Kubinka Tank Museum.
|
E791821
|
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: Kubinka | Statement: [Odintsovsky District, contains, Kubinka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kubinka Context triple: [Odintsovsky District, contains, Kubinka]
-
A.
Russas
Russas is a municipality in the northeastern Brazilian state of Ceará, known for its agricultural activities and semi-arid climate.
-
B.
Ruß
"Ruß" is a literary work by contemporary German-Turkish author Feridun Zaimoglu, known for its exploration of identity, migration, and marginalized voices in German society.
-
C.
La Russa
La Russa is an Italian surname most prominently associated with Hall of Fame Major League Baseball manager Tony La Russa.
-
D.
Kuba
Kuba is a Bantu language spoken by the Kuba people of Central Africa, known for its rich oral traditions and cultural heritage.
-
E.
Rusa
Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
- 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: Kubinka Triple: [Odintsovsky District, contains, Kubinka]
Generated description
Kubinka is a town in Moscow Oblast, Russia, best known for its large military airbase and the renowned Kubinka Tank Museum.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kubinka Target entity description: Kubinka is a town in Moscow Oblast, Russia, best known for its large military airbase and the renowned Kubinka Tank Museum.
-
A.
Russas
Russas is a municipality in the northeastern Brazilian state of Ceará, known for its agricultural activities and semi-arid climate.
-
B.
Ruß
"Ruß" is a literary work by contemporary German-Turkish author Feridun Zaimoglu, known for its exploration of identity, migration, and marginalized voices in German society.
-
C.
La Russa
La Russa is an Italian surname most prominently associated with Hall of Fame Major League Baseball manager Tony La Russa.
-
D.
Kuba
Kuba is a Bantu language spoken by the Kuba people of Central Africa, known for its rich oral traditions and cultural heritage.
-
E.
Rusa
Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
- 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.