Triple
T5231701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drug Court of Guam |
E118125
|
entity |
| Predicate | typeOfOffensesHandled |
P31978
|
FINISHED |
| Object | nonviolent drug-related offenses |
—
|
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: nonviolent drug-related offenses | Statement: [Drug Court of Guam, typeOfOffensesHandled, nonviolent drug-related offenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOffensesHandled Context triple: [Drug Court of Guam, typeOfOffensesHandled, nonviolent drug-related offenses]
-
A.
typeOfCasesHandled
chosen
Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
-
B.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
C.
targetOffenderType
Indicates the specific category or type of offender that an action, rule, or condition is directed toward.
-
D.
numberOfArrests
Indicates the count of times an entity has been arrested.
-
E.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an offense.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0223148190be88d737c25d60d7 |
completed | March 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69bd77bf1ef08190bb3487b3f3ee088c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:49 p.m.