Triple
T20805772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States v. Ray Nagin |
E512148
|
entity |
| Predicate | timePeriodOfOffenses |
P104728
|
FINISHED |
| Object | during Ray Nagin’s tenure as Mayor of New Orleans |
—
|
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: during Ray Nagin’s tenure as Mayor of New Orleans | Statement: [United States v. Ray Nagin, timePeriodOfOffenses, during Ray Nagin’s tenure as Mayor of New Orleans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfOffenses Context triple: [United States v. Ray Nagin, timePeriodOfOffenses, during Ray Nagin’s tenure as Mayor of New Orleans]
-
A.
timeframeOfCrimes
chosen
Indicates the period or span of time during which the crimes occurred or were committed.
-
B.
numberOfArrests
Indicates the count of times an entity has been arrested.
-
C.
endTimeOfCriminalActivity
Indicates the specific time at which a criminal activity or offense comes to an end.
-
D.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an offense.
-
E.
activeYearsInCrime
Indicates the span of time during which an entity was actively involved in criminal activities.
- 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2cf1cbc819092d92625dfb107d0 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:40 p.m.