Triple
T12848070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shangani Patrol incident |
E307234
|
entity |
| Predicate | BritishSouthAfricaCompanyTroopsOutcome |
P107204
|
FINISHED |
| Object | killed |
—
|
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: killed | Statement: [Shangani Patrol incident, BritishSouthAfricaCompanyTroopsOutcome, killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BritishSouthAfricaCompanyTroopsOutcome Context triple: [Shangani Patrol incident, BritishSouthAfricaCompanyTroopsOutcome, killed]
-
A.
BoerCasualties
Indicates the number or occurrence of casualties suffered by Boer forces in a conflict or engagement.
-
B.
outcomeForBritishCommander
Indicates the result or consequence experienced by a British commander in a given event or situation.
-
C.
battleCommanderOnZuluSide
Indicates that the subject served as a commanding officer for the Zulu forces in a specific battle.
-
D.
strengthBritishForces
Indicates the numerical size or combat capacity of British military forces in a given context or operation.
-
E.
commandingOfficerBritishSide
Indicates that one entity serves as the commanding officer of another entity on the British side in a military context.
- F. None of above. chosen
Provenance (4 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:36 p.m.