Triple
T3815175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kripo |
E84234
|
entity |
| Predicate | typeOfCrimesInvestigated |
P31978
|
FINISHED |
| Object | theft |
—
|
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: theft | Statement: [Kripo, typeOfCrimesInvestigated, theft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCrimesInvestigated Context triple: [Kripo, typeOfCrimesInvestigated, theft]
-
A.
investigatedBy
Indicates that an entity is the subject of an investigation carried out by another entity.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
D.
recognitionOfCrimes
Indicates the formal acknowledgment or identification that certain actions or events constitute crimes under a legal or normative framework.
-
E.
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.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.