Triple
T25752431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidney Gottlieb |
E648501
|
entity |
| Predicate | employedMethod |
P164180
|
FINISHED |
| Object | covert human experimentation |
—
|
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: covert human experimentation | Statement: [Sidney Gottlieb, employedMethod, covert human experimentation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedMethod Context triple: [Sidney Gottlieb, employedMethod, covert human experimentation]
-
A.
employedSystem
Indicates that a system is used or operated in the context of an employment or work-related arrangement.
-
B.
employedThrough
Indicates that an entity holds a job or work position by means of, or via the arrangement of, another entity (such as an agency, contractor, or intermediary).
-
C.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
D.
employedUnder
Indicates that one entity works as an employee under the authority, supervision, or organizational structure of another entity.
-
E.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
- F. None of above. chosen
Provenance (4 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f643c204508190a43fe0ec5165b01c |
completed | May 2, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f6430975b481909191219ad13ef77e |
completed | May 2, 2026, 6:31 p.m. |
Created at: April 22, 2026, 4:36 a.m.