Triple
T12011011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clearinghouse |
E285903
|
entity |
| Predicate | containsPersonalData |
P86949
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Clearinghouse, containsPersonalData, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsPersonalData Context triple: [Clearinghouse, containsPersonalData, true]
-
A.
containsDataAbout
chosen
Indicates that one entity holds or includes information or records pertaining to another entity.
-
B.
dataSubject
Indicates that one entity is the individual to whom the personal data or information in question relates.
-
C.
privacyCharacteristic
Indicates the specific privacy-related property or feature that characterizes how information is handled, protected, or exposed in a given context.
-
D.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
E.
isPersonalTo
Indicates that something is uniquely associated with, belonging to, or intended for a specific individual, rather than being general or shared.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.