Triple
T6792510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krasnoyarsk Krai |
E155967
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kansk
Kansk is a small industrial city in eastern Siberia, Russia, known as a regional transport hub within Krasnoyarsk Krai.
|
E619923
|
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: Kansk | Statement: [Krasnoyarsk Krai, contains, Kansk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kansk Context triple: [Krasnoyarsk Krai, contains, Kansk]
-
A.
Kasdan
Kasdan is a surname most notably associated with American screenwriter, director, and producer Lawrence Kasdan, known for his work on major films such as "The Empire Strikes Back" and "Raiders of the Lost Ark."
-
B.
Kras
Kras is a karst limestone plateau region in southwestern Slovenia and northeastern Italy, renowned for its distinctive caves, sinkholes, and underground rivers that gave the term "karst" to geology.
-
C.
Kamen
Kamen is a town in North Rhine-Westphalia, Germany, known as a local industrial and transport hub in the Ruhr region.
-
D.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
-
E.
Kropinski
Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
- 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: Kansk Triple: [Krasnoyarsk Krai, contains, Kansk]
Generated description
Kansk is a small industrial city in eastern Siberia, Russia, known as a regional transport hub within Krasnoyarsk Krai.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kansk Target entity description: Kansk is a small industrial city in eastern Siberia, Russia, known as a regional transport hub within Krasnoyarsk Krai.
-
A.
Kasdan
Kasdan is a surname most notably associated with American screenwriter, director, and producer Lawrence Kasdan, known for his work on major films such as "The Empire Strikes Back" and "Raiders of the Lost Ark."
-
B.
Kras
Kras is a karst limestone plateau region in southwestern Slovenia and northeastern Italy, renowned for its distinctive caves, sinkholes, and underground rivers that gave the term "karst" to geology.
-
C.
Kamen
Kamen is a town in North Rhine-Westphalia, Germany, known as a local industrial and transport hub in the Ruhr region.
-
D.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
-
E.
Kropinski
Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ae4d1c819089ac6b3abf11a341 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a8eaefc819098e848b3012da749 |
completed | March 28, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69c71ba85f608190b372a4dfe2cdc31c |
completed | March 28, 2026, 12:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c71c91e08c81908be81efc2087464a |
completed | March 28, 2026, 12:10 a.m. |
Created at: March 27, 2026, 2:15 p.m.