Triple
T34110405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supayagyi |
E874822
|
entity |
| Predicate | consortTo |
P47492
|
FINISHED |
| Object | last monarch of Burma |
—
|
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: last monarch of Burma | Statement: [Supayagyi, consortTo, last monarch of Burma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consortTo Context triple: [Supayagyi, consortTo, last monarch of Burma]
-
A.
providedConsortTo
chosen
Indicates that one entity served as the consort (spouse or partner) to another entity.
-
B.
consortInNiyoga
Indicates that one person serves as a consort to another specifically within the context of the niyoga practice (a sanctioned procreative union under prescribed social or ritual norms).
-
C.
consortToYear
Indicates the year or time period during which an entity served as consort to another.
-
D.
notableConsort
Indicates that one entity is a spouse or consort of another who is notable or significant in some recognized context.
-
E.
holderConsort
Indicates a marital or consort relationship in which one entity is the spouse or consort of the title- or office-holding entity.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70cb47b9c8190a479877960b256a6 |
completed | May 3, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:53 a.m.