Triple
T28896060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dotemu |
E732835
|
entity |
| Predicate | roleInTMNTShreddersRevenge |
P197590
|
FINISHED |
| Object | publisher |
—
|
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: publisher | Statement: [Dotemu, roleInTMNTShreddersRevenge, publisher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTMNTShreddersRevenge Context triple: [Dotemu, roleInTMNTShreddersRevenge, publisher]
-
A.
roleInScoobyDoo
Indicates the specific function or character part an entity plays within the Scooby-Doo franchise or storyline.
-
B.
roleInScoobyDoo2MonstersUnleashed
Indicates that an entity has a specific role or appearance in the film "Scooby-Doo 2: Monsters Unleashed."
-
C.
roleInTransformers
Indicates that an entity has a specific role or function within the Transformers franchise or universe.
-
D.
roleInKungFuPanda3
Indicates that an entity participated in the movie "Kung Fu Panda 3" in a specific role (such as actor, voice actor, or production role).
-
E.
roleInMonsterVerse
Indicates that an entity has a specific role or function within the MonsterVerse franchise or universe.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
| PDg | Predicate description generation | batch_69fe9df9561c8190a068f91c9fc78e56 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 28, 2026, 7:59 a.m.