Triple
T5334482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin "Buggsy" Goldstein |
E123791
|
entity |
| Predicate | legalPenalty |
P36372
|
FINISHED |
| Object | death sentence |
—
|
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: death sentence | Statement: [Martin "Buggsy" Goldstein, legalPenalty, death sentence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalPenalty Context triple: [Martin "Buggsy" Goldstein, legalPenalty, death sentence]
-
A.
legalCharge
Indicates that an authority has formally accused an entity of committing a specific legal offense or violation.
-
B.
penaltyProvision
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
C.
legalConstraint
Indicates that one entity imposes or is subject to a rule, restriction, or requirement defined by a legal or regulatory framework in relation to another entity or action.
-
D.
violationConsequences
chosen
Indicates the negative outcomes, penalties, or repercussions that result from a violation of a rule, law, or agreement.
-
E.
legalAct
Indicates that an entity performs, enacts, or is involved in a formal legal action, measure, or proceeding under a legal framework.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ae52c08190968a5567b7e6b794 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.