Triple
T9204087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kacha River |
E220924
|
entity |
| Predicate | hasNameInRussian |
P20560
|
FINISHED |
| Object |
Кача
Кача — это река в России, протекающая по Красноярскому краю и впадающая в Енисей.
|
E783432
|
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: Кача | Statement: [Kacha River, hasNameInRussian, Кача]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Кача Context triple: [Kacha River, hasNameInRussian, Кача]
-
A.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
B.
Catequil
Catequil is a thunder and lightning deity from Andean mythology, revered as a powerful weather god associated with storms and divine messages.
-
C.
Cauqui
Cauqui is an indigenous Aymaran language variety spoken by a small community in the Andean region of Peru.
-
D.
Cajeme
Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
-
E.
Taquara
Taquara is a residential neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its mix of urban development and remaining green areas.
- 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: Кача Triple: [Kacha River, hasNameInRussian, Кача]
Generated description
Кача — это река в России, протекающая по Красноярскому краю и впадающая в Енисей.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Кача Target entity description: Кача — это река в России, протекающая по Красноярскому краю и впадающая в Енисей.
-
A.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
B.
Catequil
Catequil is a thunder and lightning deity from Andean mythology, revered as a powerful weather god associated with storms and divine messages.
-
C.
Cauqui
Cauqui is an indigenous Aymaran language variety spoken by a small community in the Andean region of Peru.
-
D.
Cajeme
Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
-
E.
Taquara
Taquara is a residential neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its mix of urban development and remaining green areas.
- 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_69ca83e8e9248190862cf3e41693b310 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd945f37881909f0d30eeb6a7a3ad |
completed | April 1, 2026, 8:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c4e56208190a5b2749b81e467be |
completed | April 4, 2026, 12:33 a.m. |
| NEDg | Description generation | batch_69d05d2e27a081909497f48f3b93b1fe |
completed | April 4, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d05df1a0888190a2bdc48a159b865e |
completed | April 4, 2026, 12:40 a.m. |
Created at: March 30, 2026, 7:26 p.m.