Triple
T2019469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kwame Kilpatrick |
E44070
|
entity |
| Predicate | dateOfPerjuryConviction |
P9179
|
FINISHED |
| Object | 2008-09-04 |
—
|
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: 2008-09-04 | Statement: [Kwame Kilpatrick, dateOfPerjuryConviction, 2008-09-04]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateOfPerjuryConviction Context triple: [Kwame Kilpatrick, dateOfPerjuryConviction, 2008-09-04]
-
A.
dateOfConviction
chosen
Indicates the specific calendar date on which a person or entity was formally found guilty of an offense.
-
B.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
C.
convictionYear
Indicates the calendar year in which an entity was formally convicted of an offense.
-
D.
hasFirstConviction
Indicates that an entity has received its first legal conviction for an offense.
-
E.
sentencedOn
Indicates that a judicial authority has formally imposed a legal sentence or punishment on an entity on a specific date.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8cfa5c88190b55bce5db968665b |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a389408190a84a54856352f15b |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.