Triple
T23709461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fitbit privacy policy |
E585817
|
entity |
| Predicate | relatedToRegulation |
P60455
|
FINISHED |
| Object | GDPR |
—
|
NE NERFINISHED |
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: GDPR | Statement: [Fitbit privacy policy, relatedToRegulation, GDPR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToRegulation Context triple: [Fitbit privacy policy, relatedToRegulation, GDPR]
-
A.
relatedRegulation
chosen
Indicates that there exists a regulatory rule, law, or directive that is associated with, governs, or is otherwise relevant to the referenced entity or activity.
-
B.
associatedWithRegulation
Indicates a relationship where something is linked to, governed by, or relevant to a specific regulation or regulatory framework.
-
C.
subjectToRegulation
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
-
D.
alsoRegulates
Indicates that an entity not only has a primary regulatory effect on a target but additionally regulates that same target through another, supplementary regulatory relationship.
-
E.
regulationImpact
Indicates how a regulation influences, constrains, or alters the behavior, performance, or outcomes associated with the related 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_69e24905f77881908194d645676acd60 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b775a4288190bbee7bd4b5bbcd75 |
completed | April 29, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:53 p.m.