Triple
T9676349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digos |
E234162
|
entity |
| Predicate | typeOfCrimeMonitored |
P77441
|
FINISHED |
| Object | terrorism-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: terrorism-related offenses | Statement: [Digos, typeOfCrimeMonitored, terrorism-related offenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCrimeMonitored Context triple: [Digos, typeOfCrimeMonitored, terrorism-related offenses]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
pursuesCrimeType
chosen
Indicates that an entity (such as a law enforcement body or individual) actively investigates, targets, or prosecutes a specified type of crime.
-
D.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
E.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6ed62081908863f2ea0e98961a |
completed | April 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:15 p.m.