Triple
T29826628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015 Myanmar general election |
E757396
|
entity |
| Predicate | ledToOffice |
P166308
|
FINISHED |
| Object | State Counsellor position for Aung San Suu Kyi |
—
|
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: State Counsellor position for Aung San Suu Kyi | Statement: [2015 Myanmar general election, ledToOffice, State Counsellor position for Aung San Suu Kyi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ledToOffice Context triple: [2015 Myanmar general election, ledToOffice, State Counsellor position for Aung San Suu Kyi]
-
A.
officeStart
Indicates the time or date at which an entity’s term, role, or period of holding office begins.
-
B.
roseFromOffice
Indicates that an entity left or departed from a particular office or position, typically marking the end of their tenure there.
-
C.
goesTo
Indicates that one entity moves or travels from its current location to another specified location or entity.
-
D.
ranForOfficeIn
chosen
Indicates that a person was a candidate seeking election to a particular office in a specified political contest or time period.
-
E.
wentTo
Indicates that one entity traveled or moved from its original location to another specified place.
- 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_69f22457c84c8190a6d9f56bc74082a9 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67598dff081908ff0ec79a48b55ec |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:32 p.m.