Triple
T21801289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 刑法 |
E538242
|
entity |
| Predicate | definesTypeOfPenalty |
P1841
|
FINISHED |
| Object | 死刑 |
—
|
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: 死刑 | Statement: [刑法, definesTypeOfPenalty, 死刑]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesTypeOfPenalty Context triple: [刑法, definesTypeOfPenalty, 死刑]
-
A.
defaultPenalty
Indicates that a standard or automatically applied penalty is imposed in the absence of a specific or overridden penalty.
-
B.
penaltyProvision
chosen
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
C.
penaltyAppliesTo
Indicates that a specific penalty is imposed on, or is relevant to, a particular entity or situation.
-
D.
penaltyRules
Indicates the rules or conditions under which penalties are defined, applied, or enforced in a given context.
-
E.
penaltyMechanism
Indicates a relationship where a rule, system, or process imposes a negative consequence or sanction in response to certain actions or conditions.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077ff986081909c984cd190167640 |
completed | April 28, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:53 p.m.