Triple
T11974561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Define and Punish Clause |
E285004
|
entity |
| Predicate | categoryOfOffenses |
P67290
|
FINISHED |
| Object | piracies |
—
|
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: piracies | Statement: [Define and Punish Clause, categoryOfOffenses, piracies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryOfOffenses Context triple: [Define and Punish Clause, categoryOfOffenses, piracies]
-
A.
includesOffenseType
chosen
Indicates that one entity contains, specifies, or is associated with a particular category or type of offense.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
D.
officerCategory
Indicates the classification or type of officer role that an individual holds within an organization or system.
-
E.
definesOffence
Indicates that one entity specifies or establishes the nature, elements, or scope of an offence associated with another 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9039107e48190ae4c4efd6257dd3c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.