Triple
T18806063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Antosca |
E459875
|
entity |
| Predicate | coCreatorOf |
P806
|
FINISHED |
| Object |
Candy
Candy is a true-crime drama miniseries that chronicles the real-life story of Texas housewife Candy Montgomery and a shocking 1980 murder.
|
E805086
|
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: Candy | Statement: [Nick Antosca, coCreatorOf, Candy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Candy Context triple: [Nick Antosca, coCreatorOf, Candy]
-
A.
Candy
"Candy" is a 1999 pop song by American singer Mandy Moore that became her breakout hit and signature early single.
-
B.
Candy
Candy is an aging ranch handyman in John Steinbeck’s novel "Of Mice and Men," known for his lost hand, his old dog, and his desperate hope to join George and Lennie’s dream of owning a farm.
-
C.
Candy
Candy is a common English surname shared by various individuals, including the late Canadian actor and comedian John Candy.
-
D.
Candy
"Candy" is a song by the band Broken Silence.
-
E.
Candy
Candy is a fictional character who appears in the setting known as Candy's Room.
- 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: Candy Triple: [Nick Antosca, coCreatorOf, Candy]
Generated description
Candy is a true-crime drama miniseries that chronicles the real-life story of Texas housewife Candy Montgomery and a shocking 1980 murder.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Candy Target entity description: Candy is a true-crime drama miniseries that chronicles the real-life story of Texas housewife Candy Montgomery and a shocking 1980 murder.
-
A.
Candy
chosen
"Candy" is a true-crime drama miniseries centered on Texas housewife Candy Montgomery, who was accused of a brutal axe murder in 1980.
-
B.
Candy
Candy is a 2006 Australian romantic drama film about a destructive heroin-fueled relationship, starring Heath Ledger and Abbie Cornish and based on Luke Davies' semi-autobiographical novel.
-
C.
Candy
Candy is one of the reckless, party-obsessed college girls at the center of the crime drama film "Spring Breakers," portrayed by Vanessa Hudgens.
-
D.
Candy
"Candy" is a 1968 satirical comedy film, loosely based on Voltaire’s "Candide," known for its psychedelic style and ensemble cast including Anita Pallenberg, Marlon Brando, and Ringo Starr.
-
E.
Candy
Candy is an aging ranch handyman in John Steinbeck’s novel "Of Mice and Men," known for his lost hand, his old dog, and his desperate hope to join George and Lennie’s dream of owning a farm.
- F. None of above.
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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d7f8d08190a3e02fab6dc40bb5 |
completed | April 20, 2026, 3:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05675ff6e88190abfa88e1085873f4 |
completed | May 14, 2026, 6:10 a.m. |
| NEDg | Description generation | batch_6a05709c4e388190a451b7b5d6195934 |
completed | May 14, 2026, 6:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05716e0e888190a1e41d5cb2f860bd |
completed | May 14, 2026, 6:53 a.m. |
Created at: April 10, 2026, 11:53 a.m.