Triple
T17103393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mbuzini, South Africa |
E415034
|
entity |
| Predicate | borderProximityInfluences |
P89746
|
FINISHED |
| Object | migration patterns |
—
|
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: migration patterns | Statement: [Mbuzini, South Africa, borderProximityInfluences, migration patterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderProximityInfluences Context triple: [Mbuzini, South Africa, borderProximityInfluences, migration patterns]
-
A.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
B.
borderIsAffectedBy
chosen
Indicates that a border’s state, condition, or characteristics are influenced or changed by another factor or event.
-
C.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
D.
borderArea
Indicates that an area lies along or near the boundary between two regions, countries, or territories.
-
E.
borderingStateInfluence
Indicates that one state exerts political, economic, social, or security-related influence on another state with which it shares a land or maritime border.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2495c88190b5b16a006a994faf |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.