Triple
T21643468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nothing Serious |
E534153
|
entity |
| Predicate | containsRecurringCharactersFrom |
P120416
|
FINISHED |
| Object | Drones Club stories |
—
|
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: Drones Club stories | Statement: [Nothing Serious, containsRecurringCharactersFrom, Drones Club stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRecurringCharactersFrom Context triple: [Nothing Serious, containsRecurringCharactersFrom, Drones Club stories]
-
A.
hasRecurringCharacterFrom
chosen
Indicates that one work or series includes a character who also appears recurrently in another work or series.
-
B.
isRecurringCharacter
Indicates that an entity appears repeatedly or regularly within a given narrative, series, or context rather than only once.
-
C.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
D.
hasRecurringProtagonists
Indicates that the same main character or set of main characters appears repeatedly across multiple works or installments in a series.
-
E.
hasRecurringSeriesProtagonists
Indicates that a recurring series features one or more protagonists who appear repeatedly across its installments.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef53930644819086b0f499e1b8ae63 |
completed | April 27, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.