Triple
T449415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prague Spring |
E7093
|
entity |
| Predicate | reformMeasure |
P7268
|
FINISHED |
| Object | relaxation of censorship |
—
|
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: relaxation of censorship | Statement: [Prague Spring, reformMeasure, relaxation of censorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reformMeasure Context triple: [Prague Spring, reformMeasure, relaxation of censorship]
-
A.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
B.
notableReform
Indicates that an entity is recognized for having initiated, led, or been central to a significant reform or transformative change in a system, policy, or institution.
-
C.
hasReformEffort
chosen
Indicates that an entity undertakes, is involved in, or is the subject of a deliberate effort to change, improve, or restructure a system, policy, or practice.
-
D.
constitutionalChange
Indicates a formal modification, addition, or removal of provisions within a constitution or foundational legal framework.
-
E.
scriptAfterReform
Indicates that one script or writing system is used after a reform or modification has been applied to another script.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef6755a08190a057e72279b70456 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede1a1108190a4a06b3416ae6156 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.