Triple
T7541960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Dark Sky Sanctuary |
E178299
|
entity |
| Predicate | emphasizesProtectionOf |
P9207
|
FINISHED |
| Object | nocturnal wildlife |
—
|
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: nocturnal wildlife | Statement: [International Dark Sky Sanctuary, emphasizesProtectionOf, nocturnal wildlife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emphasizesProtectionOf Context triple: [International Dark Sky Sanctuary, emphasizesProtectionOf, nocturnal wildlife]
-
A.
aimsToProtect
chosen
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
B.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
C.
providesProtectionAgainst
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
-
D.
protectsRight
Indicates that one entity safeguards, upholds, or defends the legal or moral rights of another entity.
-
E.
providesProtectionIn
Indicates that one entity offers protection or safeguarding to another entity within a specified context, location, or situation.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.