Triple
T17983204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roland H. Dagenhart |
E430155
|
entity |
| Predicate | caseOutcomeImpactOn |
P54758
|
FINISHED |
| Object | federal child labor legislation |
—
|
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: federal child labor legislation | Statement: [Roland H. Dagenhart, caseOutcomeImpactOn, federal child labor legislation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseOutcomeImpactOn Context triple: [Roland H. Dagenhart, caseOutcomeImpactOn, federal child labor legislation]
-
A.
impactOutcome
chosen
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
B.
outcomeOf
Indicates that one entity is the result, consequence, or product that arises from another entity, event, or process.
-
C.
outcomeInvolvement
Indicates that an entity is involved in producing, influencing, or being affected by a particular outcome or result.
-
D.
impactOnCaseFlow
Indicates how an event, action, or decision affects the progression, timing, or movement of cases through a process or system.
-
E.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b2992fe481908c0d2757b4de5bad |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.