Triple
T19314675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhaisajyaguru |
E483062
|
entity |
| Predicate | cultRegion |
P1968
|
FINISHED |
| Object | Tibet |
—
|
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: Tibet | Statement: [Bhaisajyaguru, cultRegion, Tibet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tibet Context triple: [Bhaisajyaguru, cultRegion, Tibet]
-
A.
Trashiyangtse
Trashiyangtse is a town in northeastern Bhutan known as an administrative and cultural center, noted for its traditional crafts and proximity to important religious sites.
-
B.
Wallichia
Wallichia is a genus of palms native to South and Southeast Asia, named in honor of the Danish botanist Nathaniel Wallich.
-
C.
Nepal
Nepal is a landlocked South Asian country in the Himalayas, known for Mount Everest, its rich cultural heritage, and its location between India and China.
-
D.
Bhutan
Bhutan is a small, landlocked Himalayan kingdom in South Asia known for its Buddhist culture, mountainous landscapes, and emphasis on Gross National Happiness.
-
E.
Ü-Tsang
chosen
Ü-Tsang is the central historical region of Tibet, encompassing Lhasa and serving as the traditional political and cultural heartland of Tibetan civilization.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cfec8c8190a118b327b1418150 |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 10, 2026, 1:32 p.m.