Triple
T34212761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US–California border |
E877701
|
entity |
| Predicate | hasSectionDefinedByMountainCrest |
P200809
|
FINISHED |
| Object | Sierra Nevada crest |
—
|
NE NERFINISHED |
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: Sierra Nevada crest | Statement: [US–California border, hasSectionDefinedByMountainCrest, Sierra Nevada crest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionDefinedByMountainCrest Context triple: [US–California border, hasSectionDefinedByMountainCrest, Sierra Nevada crest]
-
A.
hasMountainSections
Indicates that a route, area, or path includes one or more segments that pass through or are characterized by mountainous terrain.
-
B.
hasScenicSectionAt
Indicates that a route, path, or area contains a specific segment or location that is considered scenic at that point.
-
C.
hasMountainAccess
Indicates that an entity has the right, ability, or means to enter, use, or traverse a mountain area.
-
D.
hasMountain
Indicates that a location or region possesses or contains at least one mountain.
-
E.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffada24d188190a576a02dc280a7fb |
completed | May 9, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69ffad46d6ac819081772f408b1389d5 |
completed | May 9, 2026, 9:55 p.m. |
| PDg | Predicate description generation | batch_69ffada149748190916bfd9b87356342 |
completed | May 9, 2026, 9:56 p.m. |
Created at: May 1, 2026, 1:55 a.m.