Triple
T8170714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maung Maung Soe |
E190810
|
entity |
| Predicate | reasonForSanction |
P42046
|
FINISHED |
| Object | serious human rights abuses |
—
|
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: serious human rights abuses | Statement: [Maung Maung Soe, reasonForSanction, serious human rights abuses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForSanction Context triple: [Maung Maung Soe, reasonForSanction, serious human rights abuses]
-
A.
reasonForSanctions
chosen
Indicates the underlying cause or justification for imposing sanctions on an entity.
-
B.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
-
C.
reasonForPunishment
Indicates that one entity is the cause, justification, or grounds for another entity receiving a punishment.
-
D.
sanction
Indicates the imposition of an official penalty or restrictive measure by an authority in response to certain actions or behaviors.
-
E.
reasonForSpecialMeasures
Indicates that one entity specifies the justification or cause for which special measures or exceptional actions are taken regarding another 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb48056d0c819094575090a41e0083 |
completed | March 31, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:39 p.m.