Triple
T37718402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USA Comics #1 |
E939515
|
entity |
| Predicate | introducedCharacterType |
P198720
|
FINISHED |
| Object | speedster superhero |
—
|
LITERAL FINISHED |
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: speedster superhero | Statement: [USA Comics #1, introducedCharacterType, speedster superhero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedCharacterType Context triple: [USA Comics #1, introducedCharacterType, speedster superhero]
-
A.
introducedByCharacters
Indicates that something (such as an idea, object, or event) is brought into the narrative or context by specific characters.
-
B.
introducedByCharacter
Indicates that one character is responsible for presenting, bringing into the story, or otherwise causing another entity to be first revealed or made known.
-
C.
introducesFictionalCharacter
Indicates that one entity is responsible for first presenting or bringing a fictional character into a narrative work or story.
-
D.
introducesCharacterSpecies
Indicates that an entity presents or brings into a context the species to which a character belongs.
-
E.
recurringCharacterIntroduced
Indicates that a character is introduced in a work as one who appears repeatedly across multiple episodes, issues, or installments.
- F. None of above. chosen
Provenance (4 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
| PDg | Predicate description generation | batch_69feff703fec8190ab7d0633e0cc5459 |
completed | May 9, 2026, 9:33 a.m. |
Created at: May 3, 2026, 4:18 p.m.