Triple
T23402895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moukari |
E559553
|
entity |
| Predicate | hasCallsign |
P1565
|
FINISHED |
| Object | K9FIN |
—
|
NE NERFINISHED |
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: K9FIN | Statement: [Moukari, hasCallsign, K9FIN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K9FIN Context triple: [Moukari, hasCallsign, K9FIN]
-
A.
K9NO
K9NO is the Norwegian variant of the South Korean K9 Thunder self-propelled howitzer, customized to meet Norway’s operational and technical requirements.
-
B.
K9K
K9K is a Canadian postal code prefix assigned to part of the city of Peterborough in Ontario.
-
C.
K9FIN Moukari
chosen
K9FIN Moukari is a Finnish-modified version of the South Korean K9 Thunder self-propelled howitzer, tailored to meet Finland’s specific operational and environmental requirements.
-
D.
K-9
K-9 is a 1989 American buddy cop comedy film starring James Belushi as a detective partnered with a police dog to take down a drug dealer.
-
E.
K-9
K-9 is a robotic dog from the Doctor Who universe, known as a loyal, intelligent companion equipped with advanced technology and weaponry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4e16f9881908ea4bef465e3af11 |
completed | April 29, 2026, 6:27 a.m. |
Created at: April 17, 2026, 5:37 p.m.