Triple
T14216415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professor Marius |
E352361
|
entity |
| Predicate | createdCharacter |
P2004
|
FINISHED |
| Object | K-9 Mark I |
E71121
|
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: K-9 Mark I | Statement: [Professor Marius, createdCharacter, K-9 Mark I]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K-9 Mark I Context triple: [Professor Marius, createdCharacter, K-9 Mark I]
-
A.
K9 Mark IV
K9 Mark IV is a robotic dog companion from the Doctor Who universe, known for its advanced intelligence, loyalty, and futuristic technology.
-
B.
K9A1
K9A1 is an upgraded South Korean K9 Thunder self-propelled howitzer variant featuring improved fire control, automation, and crew ergonomics.
-
C.
K9 Vidar
K9 Vidar is an upgraded variant of the South Korean K9 Thunder self-propelled howitzer, featuring enhanced firepower, mobility, and modernized systems for improved battlefield performance.
-
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
chosen
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 (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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6210213481908fac6893e8a9f143 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280e56e0819097e2aa2b28f19257 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:06 a.m.