Triple
T19507651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Gillooly |
E488065
|
entity |
| Predicate | gavePlea |
P1780
|
FINISHED |
| Object | guilty plea in connection with the attack 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: guilty plea in connection with the attack on Nancy Kerrigan | Statement: [Jeff Gillooly, gavePlea, guilty plea in connection with the attack on Nancy Kerrigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gavePlea Context triple: [Jeff Gillooly, gavePlea, guilty plea in connection with the attack on Nancy Kerrigan]
-
A.
plea
chosen
Indicates that a defendant formally states their response (such as guilty, not guilty, or no contest) to criminal charges in a legal proceeding.
-
B.
pleadsWith
Indicates that one entity urgently and emotionally appeals to another, often requesting help, mercy, or a favorable decision.
-
C.
dateOfPlea
Indicates the specific calendar date on which a formal plea was entered in a legal proceeding.
-
D.
acquittedBy
Indicates that an entity was formally cleared of charges or blame through a decision or judgment made by another entity.
-
E.
guiltyPleaCount
Indicates the number of times an entity has entered a plea of guilty in legal proceedings.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635130e708190bb3d70e1abbade2a |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.