Triple
T25053978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Héngshān |
E627463
|
entity |
| Predicate | hasScenicAreaStatus |
P29946
|
FINISHED |
| Object | national key scenic area |
—
|
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: national key scenic area | Statement: [Héngshān, hasScenicAreaStatus, national key scenic area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicAreaStatus Context triple: [Héngshān, hasScenicAreaStatus, national key scenic area]
-
A.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
-
B.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
C.
hasNationalScenicArea
chosen
Indicates that an entity is designated as or associated with a National Scenic Area.
-
D.
hasScenicAccessTo
Indicates that one place or object provides a visually appealing or notable view of another place or object.
-
E.
hasScenicResource
Indicates that an entity possesses or is associated with a natural or visual feature valued for its aesthetic or scenic qualities.
- 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 6:09 a.m.