Triple
T7785013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalaupapa Peninsula |
E187219
|
entity |
| Predicate | reasonForRestriction |
P54347
|
FINISHED |
| Object | protection of patient privacy |
—
|
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: protection of patient privacy | Statement: [Kalaupapa Peninsula, reasonForRestriction, protection of patient privacy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForRestriction Context triple: [Kalaupapa Peninsula, reasonForRestriction, protection of patient privacy]
-
A.
hasSpeedRestrictionReason
Indicates the reason or cause for which a speed restriction has been imposed on an entity.
-
B.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
-
C.
reasonForPerformanceLimitation
Indicates that one factor serves as the cause or explanation for why a performance limitation occurs.
-
D.
regulationReason
chosen
Indicates the reason or justification for which a regulation is established, applied, or enforced in relation to an entity or activity.
-
E.
reasonForSpecialMeasures
Indicates that one entity specifies the justification or cause for which special measures or exceptional actions are taken regarding another entity.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 4:23 p.m.