Triple
T25256463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEMA |
E633185
|
entity |
| Predicate | replacedLegalNatureOf |
P6150
|
FINISHED |
| Object | criminal law framework under FERA |
—
|
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: criminal law framework under FERA | Statement: [FEMA, replacedLegalNatureOf, criminal law framework under FERA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedLegalNatureOf Context triple: [FEMA, replacedLegalNatureOf, criminal law framework under FERA]
-
A.
legalReformer
Indicates that an entity works to change, improve, or modernize laws or legal systems.
-
B.
hasLegalChange
chosen
Indicates that an entity has undergone or is associated with a modification in its legal status, rights, obligations, or regulatory conditions.
-
C.
replacedInReform
Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.
-
D.
legalStatusAfterRenaming
Indicates the legal status or classification that applies to an entity after it has undergone a renaming.
-
E.
replacedByInLawEnforcement
Indicates that one entity has been superseded or taken over by another entity within a law enforcement context, such as in role, function, or authority.
- 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:13 p.m.