Triple
T14587293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robinson-Patman Act |
E342349
|
entity |
| Predicate | enforcementType |
P18859
|
FINISHED |
| Object | civil enforcement |
—
|
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: civil enforcement | Statement: [Robinson-Patman Act, enforcementType, civil enforcement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementType Context triple: [Robinson-Patman Act, enforcementType, civil enforcement]
-
A.
enforcementStrength
Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
-
B.
enforcement
chosen
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
-
C.
enforcementModel
Indicates the method or framework by which rules, policies, or constraints are applied, monitored, and enforced within a system or interaction.
-
D.
enforcedOn
Indicates that a rule, policy, or constraint is applied with authority to a particular target or subject.
-
E.
enforcedLaw
Indicates that an authority actively applies or upholds a specific law to regulate behavior or resolve situations.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb421bb308190a457425429ef6aa5 |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.