Triple
T9836348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuwaiq escarpment |
E239109
|
entity |
| Predicate | hasScenicPoint |
P71590
|
FINISHED |
| Object | popular cliff-edge viewpoints |
—
|
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: popular cliff-edge viewpoints | Statement: [Tuwaiq escarpment, hasScenicPoint, popular cliff-edge viewpoints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicPoint Context triple: [Tuwaiq escarpment, hasScenicPoint, popular cliff-edge viewpoints]
-
A.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasScenicAccessTo
Indicates that one place or object provides a visually appealing or notable view of another place or object.
-
C.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
D.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
E.
hasScenicResource
chosen
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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb33b07688190b78a70cf535c3efc |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:33 p.m.