Triple
T5140016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buttons the Clown |
E115921
|
entity |
| Predicate | hasBackstory |
P16448
|
FINISHED |
| Object | troubled past |
—
|
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: troubled past | Statement: [Buttons the Clown, hasBackstory, troubled past]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackstory Context triple: [Buttons the Clown, hasBackstory, troubled past]
-
A.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
B.
hasProtagonistBackground
Indicates that a work or narrative features a specified background or origin story for its main protagonist.
-
C.
hasOriginStoryLocation
Indicates that an entity’s origin story takes place at or is associated with a specific location.
-
D.
hasAllyInStory
Indicates that one entity is portrayed as an ally or supportive partner of another entity within the context of a specific story or narrative.
-
E.
hasTragicPast
chosen
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.