Triple
T3903677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saur Revolution |
E90553
|
entity |
| Predicate | significantConsequence |
P42250
|
FINISHED |
| Object | precipitated the Soviet–Afghan War |
—
|
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: precipitated the Soviet–Afghan War | Statement: [Saur Revolution, significantConsequence, precipitated the Soviet–Afghan War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantConsequence Context triple: [Saur Revolution, significantConsequence, precipitated the Soviet–Afghan War]
-
A.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
majorImpact
chosen
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
-
C.
significance
Indicates that one entity holds particular importance, influence, or meaningful impact in relation to another entity or context.
-
D.
significantLoss
Indicates that an entity has experienced a major or substantial decrease in value, quantity, or status beyond a normal or minor loss.
-
E.
significantPort
Indicates that a port holds major importance in terms of trade, transportation, or strategic relevance within a given context.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.