Triple
T24404401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afobaka Dam |
E615267
|
entity |
| Predicate | hasSocialEffect |
P53074
|
FINISHED |
| Object | relocation of Maroon communities |
—
|
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: relocation of Maroon communities | Statement: [Afobaka Dam, hasSocialEffect, relocation of Maroon communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocialEffect Context triple: [Afobaka Dam, hasSocialEffect, relocation of Maroon communities]
-
A.
hasSocialInfluenceThrough
Indicates that one entity exerts social influence on another specifically by means of an intermediary channel, platform, or relationship.
-
B.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
C.
hasDirectEffect
Indicates that one entity produces an immediate and unmediated impact or change on another entity.
-
D.
hasSocialDimension
Indicates that the relationship, attribute, or phenomenon involves social aspects, interactions, or implications among individuals or groups.
-
E.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294dcf7f4819094d2a3be163a5822 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.