Triple
T30963391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Measures Act |
E788886
|
entity |
| Predicate | effectDuringOctoberCrisis |
P59615
|
FINISHED |
| Object | suspension of habeas corpus |
—
|
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: suspension of habeas corpus | Statement: [War Measures Act, effectDuringOctoberCrisis, suspension of habeas corpus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectDuringOctoberCrisis Context triple: [War Measures Act, effectDuringOctoberCrisis, suspension of habeas corpus]
-
A.
hasCrisisOf
Indicates that an entity is experiencing or undergoing a crisis specifically related to another entity or concept.
-
B.
revoltOccurredDuring
Indicates that a revolt took place within the temporal span of a specified event or period.
-
C.
crisisContext
chosen
Indicates that the relationship or action occurs within, is shaped by, or is specifically relevant to a crisis situation or emergency context.
-
D.
subsequentCrisis
Indicates that one crisis occurs after and as a consequence or continuation of another earlier crisis.
-
E.
crisisRelatedTo
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
- 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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 29, 2026, 8:54 p.m.