Triple
T8350470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinhala Only policy |
E196144
|
entity |
| Predicate | increasedEthnicTensions |
P55763
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sinhala Only policy, increasedEthnicTensions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: increasedEthnicTensions Context triple: [Sinhala Only policy, increasedEthnicTensions, true]
-
A.
hasEthnicTensionHistory
chosen
Indicates that there has been a history of conflict, strain, or hostility between ethnic groups within the referenced context.
-
B.
societalConflict
Indicates a relationship where groups or individuals within a society are in opposition or tension over values, resources, power, or social norms.
-
C.
diplomaticTensionBetween
Indicates a strained or conflict-prone diplomatic relationship existing between two entities.
-
D.
politicalConflict
Indicates a relationship where entities are engaged in opposing political positions, struggles, or disputes, often involving competition for power, influence, or policy outcomes.
-
E.
causeOfPoliticalConflict
Indicates that one entity is the source or reason for a political conflict involving 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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80181ca48190bbf2e6a6aae80d69 |
completed | March 31, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69cb70c6d0ec8190acf273b0e007b51a |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.