Triple
T965727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Thatcher government |
E20832
|
entity |
| Predicate | conflictStartTime |
P22233
|
FINISHED |
| Object | 1982 |
—
|
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: 1982 | Statement: [Margaret Thatcher government, conflictStartTime, 1982]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictStartTime Context triple: [Margaret Thatcher government, conflictStartTime, 1982]
-
A.
previousConflict
Indicates that a conflict or dispute occurred between the entities at some earlier time prior to the current context.
-
B.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
C.
endedConflict
Indicates that a previously ongoing conflict between entities has been brought to an end.
-
D.
beganDuringConflict
Indicates that the action or relationship started while a specified conflict was ongoing.
-
E.
hasOngoingConflict
Indicates that there is a current, unresolved state of opposition, dispute, or hostilities between the related entities.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b431d61481908b53490e99670363 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a42c1481908d940cbe0aefdd3b |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.