Triple
T27323470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myanmar–Laos border |
E689574
|
entity |
| Predicate | relatedConflictRisk |
P199807
|
FINISHED |
| Object | drug trafficking |
—
|
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: drug trafficking | Statement: [Myanmar–Laos border, relatedConflictRisk, drug trafficking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedConflictRisk Context triple: [Myanmar–Laos border, relatedConflictRisk, drug trafficking]
-
A.
conflictRisk
Indicates a likelihood or potential for disagreement, tension, or conflict to arise between the related entities.
-
B.
associatedConflictImpact
Indicates a relationship where an entity is linked to a specific conflict and the effects or consequences that conflict has on it.
-
C.
linkedConflict
Indicates a relationship where one conflict is directly associated with, related to, or dependent on another conflict.
-
D.
conflictSensitivity
Indicates an entity’s awareness of, responsiveness to, and efforts to minimize or avoid exacerbating existing or potential conflicts in its actions or decisions.
-
E.
mentionsConflict
Indicates that one entity refers to or discusses a dispute, disagreement, or conflict involving another entity.
- F. None of above. chosen
Provenance (4 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
| PDg | Predicate description generation | batch_69ff59b1e2ac8190bb65529e9dbbb178 |
completed | May 9, 2026, 3:58 p.m. |
Created at: April 27, 2026, 11:34 a.m.