Triple
T8219243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Police Office |
E192015
|
entity |
| Predicate | typeOfCrimeAddressed |
P7957
|
FINISHED |
| Object | organized crime |
—
|
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: organized crime | Statement: [European Police Office, typeOfCrimeAddressed, organized crime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCrimeAddressed Context triple: [European Police Office, typeOfCrimeAddressed, organized crime]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific crime.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
E.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7772b76c8190b1952650c736eb91 |
completed | March 31, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.