Triple
T413480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subcommittee on Children and Families |
E9540
|
entity |
| Predicate | hasAreaOfResponsibility |
P636
|
FINISHED |
| Object | child health |
—
|
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: child health | Statement: [Subcommittee on Children and Families, hasAreaOfResponsibility, child health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfResponsibility Context triple: [Subcommittee on Children and Families, hasAreaOfResponsibility, child health]
-
A.
responsibleFor
chosen
Indicates that one entity has a duty, obligation, or role to manage, oversee, or be accountable for another entity or outcome.
-
B.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
C.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
D.
coversPolicyArea
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
-
E.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecdc422881908910428fd1aee7c6 |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e9749234819084b0ce94faabd0b1 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.