Triple
T18557012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherry Springs State Park |
E453529
|
entity |
| Predicate | hasLightPollutionLevel |
P12262
|
FINISHED |
| Object | very low |
—
|
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: very low | Statement: [Cherry Springs State Park, hasLightPollutionLevel, very low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightPollutionLevel Context triple: [Cherry Springs State Park, hasLightPollutionLevel, very low]
-
A.
lightLevel
chosen
Indicates the intensity or amount of light present in a given context or environment.
-
B.
lightPollutionPolicy
Indicates the existence or characteristics of rules or measures governing how artificial light is used to limit or manage light pollution.
-
C.
isIlluminatedAtNight
Indicates that an entity receives or emits sufficient light to be visibly illuminated during nighttime conditions.
-
D.
apparentBrightness
Indicates how bright one object appears from the perspective or location of another, regardless of its actual intrinsic luminosity.
-
E.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53806d2a08190963f4d8e927a247f |
completed | April 19, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:39 a.m.