Triple
T19314679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhaisajyaguru |
E483062
|
entity |
| Predicate | roleInChina |
P135555
|
FINISHED |
| Object | popular object of devotional worship |
—
|
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 object of devotional worship | Statement: [Bhaisajyaguru, roleInChina, popular object of devotional worship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInChina Context triple: [Bhaisajyaguru, roleInChina, popular object of devotional worship]
-
A.
roleInTaiwan
Indicates that an entity holds or has held an official or notable role, position, or function within the political, administrative, or social context of Taiwan.
-
B.
roleInBeltAndRoad
Indicates the specific function, involvement, or capacity an entity has within the context of the Belt and Road Initiative.
-
C.
roleInVietnam
Indicates that an entity held a specific role, position, or function in the context of the Vietnam War or in Vietnam-related activities.
-
D.
roleInPhilippines
Indicates that an entity holds or has held an official or notable role, position, or function within the Philippines.
-
E.
positionOnChina
Indicates the stance, opinion, or policy that one entity holds regarding China.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cfec8c8190a118b327b1418150 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4e4709d4481908c280cdd2ac18977 |
completed | April 19, 2026, 2:19 p.m. |
Created at: April 10, 2026, 1:32 p.m.