Triple
T11778818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obsidian Limited Entry Area |
E280085
|
entity |
| Predicate | hasRegulationReason |
P54347
|
FINISHED |
| Object | high visitor demand |
—
|
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: high visitor demand | Statement: [Obsidian Limited Entry Area, hasRegulationReason, high visitor demand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegulationReason Context triple: [Obsidian Limited Entry Area, hasRegulationReason, high visitor demand]
-
A.
regulationReason
chosen
Indicates the reason or justification for which a regulation is established, applied, or enforced in relation to an entity or activity.
-
B.
hasRegulations
Indicates that one entity imposes, contains, or is associated with rules or regulatory requirements that govern the behavior or operation of another entity.
-
C.
hasRegulatedBy
Indicates that one entity is subject to control, governance, or rules imposed by another entity.
-
D.
supportsRegulation
Indicates that one entity endorses, backs, or advocates for the implementation or continuation of a specific regulation.
-
E.
subjectToRegulation
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:42 p.m.