Triple
T30583193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juvenile protection units |
E778436
|
entity |
| Predicate | targetsCrimes |
P7957
|
FINISHED |
| Object | child abuse |
—
|
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: child abuse | Statement: [Juvenile protection units, targetsCrimes, child abuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsCrimes Context triple: [Juvenile protection units, targetsCrimes, child abuse]
-
A.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
B.
crimeType
chosen
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.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
E.
plansCrimeType
Indicates that an entity is planning or intending to commit a particular type or category of crime.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 29, 2026, 8:23 p.m.