Triple
T29361346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethiopia and Eritrea |
E744598
|
entity |
| Predicate | economicImpactOfConflict |
P164812
|
FINISHED |
| Object | severe disruption of cross‑border trade |
—
|
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: severe disruption of cross‑border trade | Statement: [Ethiopia and Eritrea, economicImpactOfConflict, severe disruption of cross‑border trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicImpactOfConflict Context triple: [Ethiopia and Eritrea, economicImpactOfConflict, severe disruption of cross‑border trade]
-
A.
impactOnEconomy
chosen
Indicates the effect or influence that one factor, event, or action has on the state or performance of an economy.
-
B.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
C.
stanceOnEconomy
Indicates a subject's expressed position, opinion, or policy view regarding economic issues or economic policy.
-
D.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
E.
civilianImpact
Indicates the extent to which an action, event, or situation affects civilians, especially in terms of harm, disruption, or other consequences.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 2:18 p.m.