Triple
T11680999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | eastern frontier of the Cape Colony |
E277612
|
entity |
| Predicate | mainCauseOfConflict |
P61068
|
FINISHED |
| Object | competition for land |
—
|
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: competition for land | Statement: [eastern frontier of the Cape Colony, mainCauseOfConflict, competition for land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCauseOfConflict Context triple: [eastern frontier of the Cape Colony, mainCauseOfConflict, competition for land]
-
A.
causeOfPoliticalConflict
Indicates that one entity is the source or reason for a political conflict involving another entity.
-
B.
hasCauseOfConflict
chosen
Indicates a relationship where one entity is the source or reason for a conflict involving another entity.
-
C.
mainConflict
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
D.
politicalConflict
Indicates a relationship where entities are engaged in opposing political positions, struggles, or disputes, often involving competition for power, influence, or policy outcomes.
-
E.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a461b0908190bef4e1c6777affcf |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.