Triple
T11850090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knysna Elephant Park |
E281884
|
entity |
| Predicate | ethicalPolicy |
P101851
|
FINISHED |
| Object | no elephant hunting |
—
|
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: no elephant hunting | Statement: [Knysna Elephant Park, ethicalPolicy, no elephant hunting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethicalPolicy Context triple: [Knysna Elephant Park, ethicalPolicy, no elephant hunting]
-
A.
explainsPolicy
Indicates that one entity provides a clarification or detailed description of a policy to another entity.
-
B.
issuesPolicyOn
Indicates that an authority or organization formally creates, approves, or enacts a policy concerning a particular subject or domain.
-
C.
commercialPolicy
Indicates that there is a defined set of commercial terms, rules, or conditions governing transactions or business interactions between the related entities.
-
D.
contactPolicy
Indicates the rules or constraints governing how and when one party is allowed to initiate or maintain contact with another.
-
E.
dataPolicy
Indicates that one entity defines or governs how data related to another entity is collected, used, stored, or shared.
- F. None of above. chosen
Provenance (4 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65db52c8190a218736da17d0153 |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.