Triple
T4486516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonny Bono Copyright Term Extension Act |
E107252
|
entity |
| Predicate | previousCorporateTerm |
P56848
|
FINISHED |
| Object | 75 years from publication |
—
|
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: 75 years from publication | Statement: [Sonny Bono Copyright Term Extension Act, previousCorporateTerm, 75 years from publication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousCorporateTerm Context triple: [Sonny Bono Copyright Term Extension Act, previousCorporateTerm, 75 years from publication]
-
A.
isCorporatePrecursorOf
Indicates that one corporate entity is a predecessor in the organizational or legal lineage of another corporate entity, such as through merger, acquisition, or reorganization.
-
B.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
C.
typicalTerm
Indicates that something is a standard, representative, or characteristic term typically associated with a given concept or context.
-
D.
formerEmployer
Indicates that one entity previously employed the other but no longer does so.
-
E.
previousCoCEOWith
Indicates that two entities previously served together as co-chief executive officers of the same organization.
- F. None of above. chosen
Provenance (4 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd556b93cc8190ab817d2817109a0b |
completed | March 20, 2026, 2:10 p.m. |
Created at: March 20, 2026, 12:59 p.m.