Triple
T38320176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treason Felony Act 1848 |
E1036642
|
entity |
| Predicate | containsOffenceOf |
P67290
|
FINISHED |
| Object | treason felony |
—
|
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: treason felony | Statement: [Treason Felony Act 1848, containsOffenceOf, treason felony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsOffenceOf Context triple: [Treason Felony Act 1848, containsOffenceOf, treason felony]
-
A.
includesOffenseType
chosen
Indicates that one entity contains, specifies, or is associated with a particular category or type of offense.
-
B.
definesOffence
Indicates that one entity specifies or establishes the nature, elements, or scope of an offence associated with another entity.
-
C.
offenceCognizable
Indicates that the offence is of a type for which police may initiate investigation and arrest without requiring prior permission or a warrant from a magistrate.
-
D.
typeOfOffenseAddressed
Indicates the specific category or kind of offense that a given action, measure, or legal provision is intended to address.
-
E.
legalStatusOfOffence
Indicates the legal classification or status assigned to a particular offence (e.g., whether and how it is recognized or treated under law).
- 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a02145017b08190bd424cc647c08d3b |
completed | May 11, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_6a021338e2b08190980c489ee44c18b3 |
completed | May 11, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4:30 p.m.