Triple
T18509346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Walter Hauser as Shawn Eckhardt |
E452292
|
entity |
| Predicate | partOfStoryOf |
P38554
|
FINISHED |
| Object | Tonya Harding scandal |
—
|
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: Tonya Harding scandal | Statement: [Paul Walter Hauser as Shawn Eckhardt, partOfStoryOf, Tonya Harding scandal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfStoryOf Context triple: [Paul Walter Hauser as Shawn Eckhardt, partOfStoryOf, Tonya Harding scandal]
-
A.
partOfPlot
Indicates that one event, action, or element is a constituent component within the overall plot of a narrative.
-
B.
appearsInShortStoryBy
Indicates that one entity is a character, element, or subject that appears within a short story authored by another entity.
-
C.
hasPartInNarrative
chosen
Indicates that one entity plays a role or participates as a component within the storyline or structure of another narrative entity.
-
D.
associatedTale
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
E.
associatedWithPersonInStory
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53344c6b081908e780ed5c815a766 |
completed | April 19, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69e469dbf5208190b6fc49e02a087f54 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:36 a.m.