Triple
T2460551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Impeachment of the President of India |
E54522
|
entity |
| Predicate | safeguard |
P40653
|
FINISHED |
| Object | strict procedural requirements |
—
|
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: strict procedural requirements | Statement: [Impeachment of the President of India, safeguard, strict procedural requirements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safeguard Context triple: [Impeachment of the President of India, safeguard, strict procedural requirements]
-
A.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
D.
safeguardingMeasuresInclude
Indicates that certain specific protective or security measures are contained within, or form part of, a broader set of safeguarding measures.
-
E.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.