Triple
T12848069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shangani Patrol incident |
E307234
|
entity |
| Predicate | numberOfBritishSouthAfricaCompanyTroops |
P6153
|
FINISHED |
| Object | about 34 |
—
|
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: about 34 | Statement: [Shangani Patrol incident, numberOfBritishSouthAfricaCompanyTroops, about 34]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBritishSouthAfricaCompanyTroops Context triple: [Shangani Patrol incident, numberOfBritishSouthAfricaCompanyTroops, about 34]
-
A.
strengthBritishForces
Indicates the numerical size or combat capacity of British military forces in a given context or operation.
-
B.
BritishForcesType
Indicates that an entity is classified as a type or category within the British armed forces.
-
C.
numberOfRegimentsInvolved
Indicates the total count of regiments that participated in or were involved in a specified event or action.
-
D.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
E.
militaryForceInvolved (British)
Indicates that the British military forces participated in or were involved in the referenced event or action.
- 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_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. |
Created at: April 9, 2026, 5:36 p.m.