Triple
T23390935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natal region |
E594014
|
entity |
| Predicate | wasBoerRepublicInfluenced |
P12632
|
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: [Natal region, wasBoerRepublicInfluenced, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasBoerRepublicInfluenced Context triple: [Natal region, wasBoerRepublicInfluenced, true]
-
A.
BoerCasualties
Indicates the number or occurrence of casualties suffered by Boer forces in a conflict or engagement.
-
B.
effectOnDutchRepublic
Indicates the impact or consequences that something has on the Dutch Republic.
-
C.
historicalColonialEntityOnZimbabweSide
Indicates that the subject was a historical colonial entity located on, controlling, or associated with the territory that is now Zimbabwe.
-
D.
legalStatusUnderApartheid
Indicates the legal classification or rights a person or group held under apartheid-era laws and policies.
-
E.
hasHistoricalInfluenceFrom
chosen
Indicates that one entity’s characteristics, development, or significance have been shaped or affected by the past actions, ideas, or legacy of 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49bdfec8190afa592c66660c279 |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:36 p.m.