Triple
T9126298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burmese nationalism |
E218974
|
entity |
| Predicate | hasTensionWith |
P61198
|
FINISHED |
| Object | federalism demands of ethnic minorities |
—
|
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: federalism demands of ethnic minorities | Statement: [Burmese nationalism, hasTensionWith, federalism demands of ethnic minorities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTensionWith Context triple: [Burmese nationalism, hasTensionWith, federalism demands of ethnic minorities]
-
A.
hasTension
chosen
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
B.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
C.
tensionArea
Indicates the region or extent over which mechanical or emotional tension is distributed or experienced.
-
D.
hasTendency
Indicates that an entity is inclined or likely to exhibit a particular behavior, characteristic, or outcome under certain conditions.
-
E.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
- 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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8c93d3c8190b003b2b1af2003b2 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:18 p.m.