Triple
T5885428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Minister of India |
E130848
|
entity |
| Predicate | appointmentTerm |
P67267
|
FINISHED |
| Object | serves at the pleasure of the President |
—
|
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: serves at the pleasure of the President | Statement: [Deputy Minister of India, appointmentTerm, serves at the pleasure of the President]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appointmentTerm Context triple: [Deputy Minister of India, appointmentTerm, serves at the pleasure of the President]
-
A.
appointmentBy
Indicates that one entity is appointed or designated to a role, position, or task by another entity.
-
B.
appointmentType
Indicates the specific category or nature of an appointment associated with an entity or event.
-
C.
appointmentBody
Indicates that one entity serves as the main content or body text associated with a particular appointment.
-
D.
appointmentOnAdviceOf
Indicates that an appointment or selection of someone to a position is made based on the recommendation, counsel, or formal advice of another person or authority.
-
E.
appointmentProcessIncludes
Indicates that an appointment process contains or encompasses a specific step, activity, or component as part of its overall workflow.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03fdf954c8190ae97a5c9ce40bdfa |
completed | March 22, 2026, 7:15 p.m. |
Created at: March 22, 2026, 3:57 p.m.