Triple
T9862236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reichenau Order |
E239742
|
entity |
| Predicate | typeOfCrimeFacilitated |
P7957
|
FINISHED |
| Object | mass shootings |
—
|
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: mass shootings | Statement: [Reichenau Order, typeOfCrimeFacilitated, mass shootings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCrimeFacilitated Context triple: [Reichenau Order, typeOfCrimeFacilitated, mass shootings]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
roleInCrime
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
isCriminalizedIn
Indicates that a specific behavior, action, or condition is prohibited and subject to legal penalties within a particular jurisdiction or legal system.
-
E.
country of criminal activity
Indicates the country in which the criminal activity took place or was primarily carried out.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3b7b81c81909a84f6ced829f394 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:35 p.m.