Triple
T37228498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Perils of Penelope Pitstop |
E923067
|
entity |
| Predicate | villainAlterEgoOf |
P86336
|
FINISHED |
| Object | Sylvester Sneekly |
—
|
NE NERFINISHED |
How this triple was built (2 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: Sylvester Sneekly | Statement: [The Perils of Penelope Pitstop, villainAlterEgoOf, Sylvester Sneekly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: villainAlterEgoOf Context triple: [The Perils of Penelope Pitstop, villainAlterEgoOf, Sylvester Sneekly]
-
A.
antagonistAlterEgoOf
Indicates that one entity serves as the primary opposing force or enemy of another entity’s alternate identity or secret persona.
-
B.
hasFictionalAlterEgoOf
chosen
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
C.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
D.
nicknameOfAntagonist
Indicates that one entity is a nickname or informal name used for an antagonist entity in a work or context.
-
E.
supervillainName
Indicates that an entity is known by a particular supervillain name or alias.
- F. None of above.
Provenance (3 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.