Triple
T35216372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reggie and the Full Effect |
E1016823
|
entity |
| Predicate | hasFictionalPersona |
P25662
|
FINISHED |
| Object | Fluxuation |
—
|
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: Fluxuation | Statement: [Reggie and the Full Effect, hasFictionalPersona, Fluxuation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPersona Context triple: [Reggie and the Full Effect, hasFictionalPersona, Fluxuation]
-
A.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
-
B.
hasFictionalLeadCharacter
Indicates that a creative work features a particular fictional character as its main or leading protagonist.
-
C.
hasFictionalSpeaker
Indicates that a work, text, or expression is presented as being spoken by an invented or non-real speaker rather than an actual person.
-
D.
hasFictionalRole
chosen
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
E.
hasFictionalSpokesperson
Indicates that an entity is represented or promoted by a spokesperson who is a fictional or imaginary character.
- 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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: May 3, 2026, 4:02 p.m.