Triple
T26103285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Flynn |
E658471
|
entity |
| Predicate | pleadedGuilty |
P159943
|
FINISHED |
| Object | 2017-12 |
—
|
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: 2017-12 | Statement: [Michael Flynn, pleadedGuilty, 2017-12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pleadedGuilty Context triple: [Michael Flynn, pleadedGuilty, 2017-12]
-
A.
guiltyPleaCount
Indicates the number of times an entity has entered a plea of guilty in legal proceedings.
-
B.
confessedTo
Indicates that one entity admitted guilt or revealed the truth about an action, wrongdoing, or secret to another entity.
-
C.
guiltyOf
Indicates that an entity has been judged or determined to have committed a particular offense, crime, or wrongful act.
-
D.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
E.
convictedBy
Indicates that an authority, typically a court or judge, has formally found an entity guilty of a crime or offense.
- 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6077370d081908074987cb49c4ee9 |
completed | May 2, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 7:56 p.m.