Triple
T15763370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donkey Kong universe |
E382153
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Krusha |
E1162408
|
NE FINISHED |
How this triple was built (2 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: Krusha | Statement: [Donkey Kong universe, hasCharacter, Krusha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krusha Context triple: [Donkey Kong universe, hasCharacter, Krusha]
-
A.
Krusha
chosen
Krusha is a large, muscular Kremling character from the Donkey Kong video game series, typically depicted as a strong but dim-witted enemy.
-
B.
Nishani
Nishani is an Albanian surname most notably borne by Bujar Nishani, a former President of Albania.
-
C.
Wonokitri
Wonokitri is a village in East Java, Indonesia, known as a gateway settlement for visitors heading to the Mount Bromo area.
-
D.
Krorayina
Krorayina is an ancient oasis city in the Tarim Basin of present-day Xinjiang, China, known for its role as a Silk Road trading center and its well-preserved archaeological remains.
-
E.
Magarima
Magarima is a small town in Papua New Guinea’s Hela Province, serving as a local administrative and service center for surrounding rural communities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8776c2488190ad27fd79e2ce4e14 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.