Triple
T18509365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Walter Hauser as Shawn Eckhardt |
E452292
|
entity |
| Predicate | characterInvolvement |
P95262
|
FINISHED |
| Object | planning of assault on Nancy Kerrigan |
—
|
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: planning of assault on Nancy Kerrigan | Statement: [Paul Walter Hauser as Shawn Eckhardt, characterInvolvement, planning of assault on Nancy Kerrigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInvolvement Context triple: [Paul Walter Hauser as Shawn Eckhardt, characterInvolvement, planning of assault on Nancy Kerrigan]
-
A.
involvedActor
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
B.
plotCharacter
chosen
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
C.
plotInvolvement
Indicates that an entity participates in, contributes to, or is affected by the events or storyline of a narrative work.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
characterStatusInStory
Indicates the role or condition a character holds within the context of a specific story or narrative.
- 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.