Triple
T12755645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Palko |
E304851
|
entity |
| Predicate | hasRightAtIssue |
P21381
|
FINISHED |
| Object | protection against double jeopardy |
—
|
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: protection against double jeopardy | Statement: [Frank Palko, hasRightAtIssue, protection against double jeopardy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRightAtIssue Context triple: [Frank Palko, hasRightAtIssue, protection against double jeopardy]
-
A.
hasLegalRight
chosen
Indicates that an entity possesses an officially recognized legal entitlement or permission to perform an action or hold a claim regarding another entity.
-
B.
hasKeyIssue
Indicates that an entity is associated with a primary or central problem, concern, or topic of importance.
-
C.
hasRightsOver
Indicates that one entity possesses legal, moral, or formal entitlements or authority over another entity.
-
D.
hasLegalIssue
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
E.
hasNoIssue
Indicates that there are no problems, defects, or conflicts associated with the referenced entity or situation.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8b57b88190b29b8fdca415c81c |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.