Triple
T12419040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John F. Link |
E296716
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
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.
|
E980370
|
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: K-9 | Statement: [John F. Link, notableWork, K-9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K-9 Context triple: [John F. Link, notableWork, K-9]
-
A.
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.
-
B.
K9K
K9K is a Canadian postal code prefix assigned to part of the city of Peterborough in Ontario.
-
C.
K-99
K-99 is a north–south state highway running through eastern Kansas, connecting several small towns and rural areas.
-
D.
Pooch
Pooch is a skilled and resourceful member of the elite black-ops team in the action film "The Losers."
-
E.
K-9 and Company
K-9 and Company is a British science-fiction television series set in the Doctor Who universe, featuring the Doctor’s robotic dog K-9 and former companion Sarah Jane Smith in their own adventures.
- 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: K-9 Triple: [John F. Link, notableWork, K-9]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: K-9 Target entity description: 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.
-
A.
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.
-
B.
K9K
K9K is a Canadian postal code prefix assigned to part of the city of Peterborough in Ontario.
-
C.
K-99
K-99 is a north–south state highway running through eastern Kansas, connecting several small towns and rural areas.
-
D.
Pooch
Pooch is a skilled and resourceful member of the elite black-ops team in the action film "The Losers."
-
E.
K-9 and Company
K-9 and Company is a British science-fiction television series set in the Doctor Who universe, featuring the Doctor’s robotic dog K-9 and former companion Sarah Jane Smith in their own adventures.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6efd748190a5d9396a343e41e1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634933b9881909fd592ede7c3e49c |
completed | May 2, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69f6356c21908190b34d1324da8f8052 |
completed | May 2, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f63693f5c881909a9683a0c6a68739 |
completed | May 2, 2026, 5:38 p.m. |
Created at: April 8, 2026, 9:55 p.m.