Triple
T343788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siete Leyes |
E6893
|
entity |
| Predicate | effectOnStates |
P1634
|
FINISHED |
| Object | reduced regional autonomy |
—
|
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: reduced regional autonomy | Statement: [Siete Leyes, effectOnStates, reduced regional autonomy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnStates Context triple: [Siete Leyes, effectOnStates, reduced regional autonomy]
-
A.
appliedToStatesThrough
Indicates that something (such as a rule, policy, or process) is implemented or enforced by means of, or via the mediation of, particular states.
-
B.
associatedState
Indicates that one entity is linked or connected to a particular state, condition, or status of another entity.
-
C.
effectOfDesignation
Indicates the causal impact or consequences that a particular designation or assigned status has on something.
-
D.
hasLegalEffect
Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
-
E.
primaryEffect
chosen
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb0019088190a9b969c4287dc4fa |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e9530c98819085025efe4e04aa7e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.