Triple
T32904645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grin of the Dark |
E841701
|
entity |
| Predicate | fictionalComedian |
P43063
|
FINISHED |
| Object | Tubby Thackeray |
—
|
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: Tubby Thackeray | Statement: [The Grin of the Dark, fictionalComedian, Tubby Thackeray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalComedian Context triple: [The Grin of the Dark, fictionalComedian, Tubby Thackeray]
-
A.
comedian
Indicates that the subject performs comedy or is recognized for engaging in comedic entertainment.
-
B.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
C.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
D.
fictionalCharacterFrom
chosen
Indicates that a fictional character originates from, or is created within, a particular work, universe, or source.
-
E.
fictionalPlayer
Indicates that the referenced player entity is imaginary or does not exist in the real world, but is instead part of a fictional or simulated context.
- 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_69f34946a5208190bbd79f0fec4323bd |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: May 1, 2026, 1:19 a.m.