Triple
T28966474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John–Furnish family |
E732052
|
entity |
| Predicate | knownForPrivacyConcerns |
P171948
|
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: [John–Furnish family, knownForPrivacyConcerns, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForPrivacyConcerns Context triple: [John–Furnish family, knownForPrivacyConcerns, true]
-
A.
privacyIssue
chosen
Indicates that an action, condition, or relationship involves a violation, risk, or concern related to the protection or appropriate handling of personal or sensitive information.
-
B.
privacyCharacteristic
Indicates the specific privacy-related property or feature that characterizes how information is handled, protected, or exposed in a given context.
-
C.
soughtPrivacy
Indicates that an entity intentionally attempted to obtain or maintain privacy from others.
-
D.
notableWhistleblower
Indicates that the subject is recognized for having exposed significant wrongdoing or misconduct, typically within an organization or institution.
-
E.
hasBeenSubjectOf
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
- 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 28, 2026, 8:52 a.m.