Triple
T13817333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Courts of First Instance (Peru) |
E332050
|
entity |
| Predicate | canApply |
P104189
|
FINISHED |
| Object | Peruvian substantive law |
—
|
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: Peruvian substantive law | Statement: [Courts of First Instance (Peru), canApply, Peruvian substantive law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canApply Context triple: [Courts of First Instance (Peru), canApply, Peruvian substantive law]
-
A.
canApplyFor
Indicates that one entity has the eligibility or permission to submit a request or application for another entity or opportunity.
-
B.
mayApply
chosen
Indicates that an entity is permitted or eligible to submit or use something (such as a rule, action, or resource) under certain conditions.
-
C.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
D.
appliesVia
Indicates that an action, rule, or effect is carried out, implemented, or achieved through a specified method, medium, or mechanism.
-
E.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0281bb988190803ee195f430b9c8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.