Triple
T18474706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adrian Lester |
E451398
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Trigger Point
Trigger Point is a British crime drama television series centered on bomb disposal experts in London, known for its tense, high-stakes storytelling.
|
E1326654
|
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 Point | Statement: [Adrian Lester, notableWork, Trigger Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trigger Point Context triple: [Adrian Lester, notableWork, Trigger Point]
-
A.
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.
-
B.
Trigger
"Trigger" is a popular melodic death metal song by Swedish band In Flames, known for its aggressive riffs and catchy choruses.
-
C.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
D.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
E.
Dead Point
"Dead Point" is a crime novel in the Jack Irish series by Australian author Peter Temple, featuring the eponymous lawyer-turned-investigator navigating Melbourne’s criminal underworld.
- 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 Point Triple: [Adrian Lester, notableWork, Trigger Point]
Generated description
Trigger Point is a British crime drama television series centered on bomb disposal experts in London, known for its tense, high-stakes storytelling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trigger Point Target entity description: Trigger Point is a British crime drama television series centered on bomb disposal experts in London, known for its tense, high-stakes storytelling.
-
A.
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.
-
B.
Trigger
"Trigger" is a popular melodic death metal song by Swedish band In Flames, known for its aggressive riffs and catchy choruses.
-
C.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
D.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
E.
Dead Point
"Dead Point" is a crime novel in the Jack Irish series by Australian author Peter Temple, featuring the eponymous lawyer-turned-investigator navigating Melbourne’s criminal underworld.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53062387481909d4503fc963f9913 |
completed | April 19, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a043f2ae2888190ae12fee12cf419ff |
completed | May 13, 2026, 9:06 a.m. |
| NEDg | Description generation | batch_6a043fd646b88190b0d232e740ae22ba |
completed | May 13, 2026, 9:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04403951608190bc24c914175f18bc |
completed | May 13, 2026, 9:11 a.m. |
Created at: April 10, 2026, 11:34 a.m.