Triple
T3870510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Nevada University |
E91973
|
entity |
| Predicate | campusLocationDescription |
P13638
|
FINISHED |
| Object | near the shores of Lake Tahoe |
—
|
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: near the shores of Lake Tahoe | Statement: [Sierra Nevada University, campusLocationDescription, near the shores of Lake Tahoe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusLocationDescription Context triple: [Sierra Nevada University, campusLocationDescription, near the shores of Lake Tahoe]
-
A.
campusDescription
chosen
Indicates a descriptive relationship that specifies details or characteristics of a campus.
-
B.
campusAddress
Indicates that an entity has a specific address associated with a campus location.
-
C.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
-
D.
campusLandmark
Indicates that something serves as a notable or recognizable landmark located on or associated with a campus.
-
E.
cityCampus
Indicates that a campus is located within or associated with a particular city.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec54b0848190a8d4a0e4df7b6227 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.