Triple
T10396491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humans |
E245033
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Niska
Niska is a French rapper known for his energetic trap-influenced style, inventive slang, and hit tracks that have significantly impacted the Francophone hip-hop scene.
|
E860463
|
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: Niska | Statement: [Humans, hasCharacter, Niska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niska Context triple: [Humans, hasCharacter, Niska]
-
A.
Niesky
Niesky is a small town in eastern Saxony, Germany, known for its historical connections to regional conflicts and its location near the Polish border.
-
B.
Nikisch
Nikisch is a surname most notably associated with Arthur Nikisch, a renowned late 19th- and early 20th-century Hungarian conductor.
-
C.
Nuska
Nuska is a Mesopotamian god of fire and light, often serving as a divine vizier and attendant to major deities in the Sumerian and Akkadian pantheons.
-
D.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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: Niska Triple: [Humans, hasCharacter, Niska]
Generated description
Niska is a French rapper known for his energetic trap-influenced style, inventive slang, and hit tracks that have significantly impacted the Francophone hip-hop scene.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Niska Target entity description: Niska is a French rapper known for his energetic trap-influenced style, inventive slang, and hit tracks that have significantly impacted the Francophone hip-hop scene.
-
A.
Niesky
Niesky is a small town in eastern Saxony, Germany, known for its historical connections to regional conflicts and its location near the Polish border.
-
B.
Nikisch
Nikisch is a surname most notably associated with Arthur Nikisch, a renowned late 19th- and early 20th-century Hungarian conductor.
-
C.
Nuska
Nuska is a Mesopotamian god of fire and light, often serving as a divine vizier and attendant to major deities in the Sumerian and Akkadian pantheons.
-
D.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d795cf331c8190b35caf3997dc29a3 |
completed | April 9, 2026, 12:04 p.m. |
| NEDg | Description generation | batch_69d7bde050ac8190b87a0c81700ad1b1 |
completed | April 9, 2026, 2:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7e60afaf481909a0790c94e323143 |
completed | April 9, 2026, 5:46 p.m. |
Created at: April 6, 2026, 12:06 p.m.