Triple
T14959621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candid Camera |
E373029
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
Trigger Happy TV
Trigger Happy TV is a British hidden-camera comedy series known for its surreal, deadpan pranks and absurd public stunts orchestrated by comedian Dom Joly.
|
E1128968
|
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: Trigger Happy TV | Statement: [Candid Camera, influenced, Trigger Happy TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trigger Happy TV Context triple: [Candid Camera, influenced, Trigger Happy TV]
-
A.
Trigger Happy
Trigger Happy is a manic, gun-slinging gremlin Skylander known for his wild personality and rapid-fire golden pistols in the Skylanders video game series.
-
B.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
C.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
D.
Trigger
Trigger is a dim-witted yet lovable road sweeper from the British sitcom "Only Fools and Horses," known for his deadpan delivery and iconic broom joke.
-
E.
Zapping
Zapping is a Spanish film that marked the screen debut of actress Paz Vega.
- 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: Trigger Happy TV Triple: [Candid Camera, influenced, Trigger Happy TV]
Generated description
Trigger Happy TV is a British hidden-camera comedy series known for its surreal, deadpan pranks and absurd public stunts orchestrated by comedian Dom Joly.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trigger Happy TV Target entity description: Trigger Happy TV is a British hidden-camera comedy series known for its surreal, deadpan pranks and absurd public stunts orchestrated by comedian Dom Joly.
-
A.
Trigger Happy
Trigger Happy is a manic, gun-slinging gremlin Skylander known for his wild personality and rapid-fire golden pistols in the Skylanders video game series.
-
B.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
C.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
D.
Trigger
Trigger is a dim-witted yet lovable road sweeper from the British sitcom "Only Fools and Horses," known for his deadpan delivery and iconic broom joke.
-
E.
Zapping
Zapping is a Spanish film that marked the screen debut of actress Paz Vega.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7ea1d78c81909b877fda05ef9231 |
completed | May 9, 2026, 12:24 a.m. |
| NEDg | Description generation | batch_69fe7ff5c84c8190b3e97f09633bf181 |
completed | May 9, 2026, 12:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe80be100481908dcf07b683fc1411 |
completed | May 9, 2026, 12:33 a.m. |
Created at: April 10, 2026, 2:40 a.m.