Triple
T3449423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disciplinary Board of the Supreme Court of Pennsylvania |
E72756
|
entity |
| Predicate | typeOfSanctionsHandled |
P18137
|
FINISHED |
| Object | disbarment |
—
|
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: disbarment | Statement: [Disciplinary Board of the Supreme Court of Pennsylvania, typeOfSanctionsHandled, disbarment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSanctionsHandled Context triple: [Disciplinary Board of the Supreme Court of Pennsylvania, typeOfSanctionsHandled, disbarment]
-
A.
typeOfSanction
chosen
Indicates the specific category or kind of sanction that is applied in a given situation.
-
B.
countrySubjectToSanctions
Indicates that a country is currently facing formal sanctions or restrictive measures imposed by another state or international body.
-
C.
canBeSanctionedFor
Indicates that an entity is subject to penalties or disciplinary measures as a consequence of a specified action, behavior, or condition.
-
D.
canImposeSanctions
Indicates that one entity has the authority or power to apply punitive or restrictive measures (sanctions) against another entity.
-
E.
reasonForSanctions
Indicates the underlying cause or justification for imposing sanctions on an 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba71f4a4819089d08b871cc9b16f |
completed | March 8, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69adae0255b48190a9069f7871c7a012 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.