Triple
T1615317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert F. Kennedy Jr. |
E34702
|
entity |
| Predicate | stanceOnVaccines |
P17598
|
FINISHED |
| Object | opposes many childhood vaccine policies |
—
|
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: opposes many childhood vaccine policies | Statement: [Robert F. Kennedy Jr., stanceOnVaccines, opposes many childhood vaccine policies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stanceOnVaccines Context triple: [Robert F. Kennedy Jr., stanceOnVaccines, opposes many childhood vaccine policies]
-
A.
hasDifferentOpinionsOn
Indicates that two or more entities hold differing views or judgments regarding a particular topic, issue, or subject.
-
B.
stanceTowardGovernment
Indicates the attitude, position, or level of support or opposition that an entity holds toward a government.
-
C.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
D.
raisedConcernAbout
chosen
Indicates that one entity has expressed worry, doubt, or objection regarding another entity or issue.
-
E.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.