Triple
T8433157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarlet Witch |
E199163
|
entity |
| Predicate | children |
P980
|
FINISHED |
| Object |
Billy Kaplan
Billy Kaplan is a Marvel Comics superhero, also known as Wiccan, who is a powerful magic user and a member of the Young Avengers.
|
E738952
|
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: Billy Kaplan | Statement: [Scarlet Witch, children, Billy Kaplan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billy Kaplan Context triple: [Scarlet Witch, children, Billy Kaplan]
-
A.
Sol Kaplan
Sol Kaplan was an American composer best known for his film and television scores, including work in mid-20th-century Hollywood.
-
B.
Hank Kaplan
Hank Kaplan is a fictional character from the American medical drama television series "Nurses."
-
C.
Butch Kaplan
Butch Kaplan is a film and television producer known for his work on projects such as the Western miniseries "Broken Trail."
-
D.
Larry Kaplan
Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
-
E.
Greg Kaplan
Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
- 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: Billy Kaplan Triple: [Scarlet Witch, children, Billy Kaplan]
Generated description
Billy Kaplan is a Marvel Comics superhero, also known as Wiccan, who is a powerful magic user and a member of the Young Avengers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Billy Kaplan Target entity description: Billy Kaplan is a Marvel Comics superhero, also known as Wiccan, who is a powerful magic user and a member of the Young Avengers.
-
A.
Sol Kaplan
Sol Kaplan was an American composer best known for his film and television scores, including work in mid-20th-century Hollywood.
-
B.
Hank Kaplan
Hank Kaplan is a fictional character from the American medical drama television series "Nurses."
-
C.
Butch Kaplan
Butch Kaplan is a film and television producer known for his work on projects such as the Western miniseries "Broken Trail."
-
D.
Larry Kaplan
Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
-
E.
Greg Kaplan
Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd1a74d948190abd76e7a6efb42ec |
completed | March 31, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4dc163488190a53d8696fdba94b5 |
completed | April 2, 2026, 11:06 a.m. |
| NEDg | Description generation | batch_69ce51efb1e48190abca64f24b03febc |
completed | April 2, 2026, 11:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce525196208190b2d70fd2be293826 |
completed | April 2, 2026, 11:26 a.m. |
Created at: March 30, 2026, 6:07 p.m.