Triple
T29274278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randomized evaluations of health insurance expansions |
E742206
|
entity |
| Predicate | controlsFor |
P122612
|
FINISHED |
| Object | selection bias into insurance |
—
|
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: selection bias into insurance | Statement: [Randomized evaluations of health insurance expansions, controlsFor, selection bias into insurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlsFor Context triple: [Randomized evaluations of health insurance expansions, controlsFor, selection bias into insurance]
-
A.
controlsWith
Indicates that one entity exercises authority, direction, or regulatory power over another entity through specific means or mechanisms.
-
B.
controlFrom
Indicates that one entity exercises authority, influence, or regulatory power over another entity or process.
-
C.
controlsType
Indicates that one entity has authority over, or the ability to direct or regulate, the type or category of another entity.
-
D.
controlsOrControlled
Indicates that one entity has control over another entity or is itself under the control of that other entity.
-
E.
controlledFor
chosen
Indicates that the influence or effect of a specified factor has been accounted for or neutralized when assessing the relationship between other variables or entities.
- 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_69f0912124d48190a046642b69407f4c |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 28, 2026, 12:50 p.m.