Triple
T236637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Maria Theresa |
E4837
|
entity |
| Predicate | introducedPolicy |
P172
|
FINISHED |
| Object | compulsory primary education in her realms |
—
|
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: compulsory primary education in her realms | Statement: [Empress Maria Theresa, introducedPolicy, compulsory primary education in her realms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedPolicy Context triple: [Empress Maria Theresa, introducedPolicy, compulsory primary education in her realms]
-
A.
implementedPolicy
chosen
Indicates that a particular policy has been put into effect or carried out by an entity.
-
B.
governingPolicy
Indicates that one entity serves as the authoritative policy or set of rules that directs, constrains, or regulates the behavior, operation, or decisions of another entity.
-
C.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
D.
declaredPolicy
Indicates that an entity has formally stated or announced a specific policy or course of action.
-
E.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ccc5d548190b505bf1d99db41bd |
completed | Feb. 28, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69a25b5dc640819092669575731c393f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.