Triple
T19000239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian National Liberal Federation |
E464928
|
entity |
| Predicate | stanceOnViolence |
P20160
|
FINISHED |
| Object | opposed political violence |
—
|
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: opposed political violence | Statement: [Indian National Liberal Federation, stanceOnViolence, opposed political violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stanceOnViolence Context triple: [Indian National Liberal Federation, stanceOnViolence, opposed political violence]
-
A.
viewOnViolence
Indicates an entity’s stance, opinion, or attitude toward the use of violence.
-
B.
positionOnViolence
chosen
Indicates a stance, attitude, or policy that an entity holds regarding the use, justification, or acceptability of violence.
-
C.
usedViolenceAgainst
Indicates that one entity intentionally inflicted physical force or harm upon another entity.
-
D.
justifiesViolenceThrough
Indicates that one party legitimizes or defends the use of violence by appealing to, or reasoning through, another factor, belief, or circumstance.
-
E.
nonviolenceTypeDiscussed
Indicates that the discussion or communication centers on a particular type or form of nonviolence.
- 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6863cf4819096e471d19f9a714c |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f88e0c81908cb20f08bf24cd32 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.