Triple
T38079022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caturmahārāja |
E950799
|
entity |
| Predicate | equivalentTermInTibetan |
P125122
|
FINISHED |
| Object | rgyal chen bzhi |
—
|
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: rgyal chen bzhi | Statement: [Caturmahārāja, equivalentTermInTibetan, rgyal chen bzhi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentTermInTibetan Context triple: [Caturmahārāja, equivalentTermInTibetan, rgyal chen bzhi]
-
A.
equivalentInTibet
Indicates that two entities are considered equivalent or correspond to each other within the context of Tibet.
-
B.
equivalentInBuddhism
Indicates that one concept, figure, or element is regarded as the corresponding or matching counterpart within the context of Buddhism.
-
C.
nameInTibetan
chosen
Indicates that an entity’s name is expressed or written in the Tibetan language.
-
D.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
E.
equivalentEpithetLanguage
Indicates that two epithets are expressed in different languages but convey the same meaning or designation.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:21 p.m.