Triple
T14834304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qyburn |
E348787
|
entity |
| Predicate | reasonForDisgrace |
P113750
|
FINISHED |
| Object | unethical experiments on living subjects |
—
|
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: unethical experiments on living subjects | Statement: [Qyburn, reasonForDisgrace, unethical experiments on living subjects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForDisgrace Context triple: [Qyburn, reasonForDisgrace, unethical experiments on living subjects]
-
A.
disgracedFor
chosen
Indicates that an entity has lost honor, respect, or status specifically because of the associated reason, action, or circumstance.
-
B.
causeOfReputation
Indicates that one entity is the reason or source for another entity’s reputation.
-
C.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
-
D.
subjectOfCondemnation
Indicates that one entity is the target or object of formal disapproval, criticism, or denunciation by another entity.
-
E.
causeOfLegalCondemnation
Indicates that one entity is the reason or basis for another entity being legally condemned, judged guilty, or subjected to legal penalties.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded076ac9c8190a05cabec5e87d207 |
completed | April 14, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69de8c13418c819088ff9905ace1416a |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:52 a.m.