Triple
T31219679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danie Theron Combat School |
E795971
|
entity |
| Predicate | namesakeNotableFor |
P65175
|
FINISHED |
| Object | service in the Second Boer War |
—
|
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: service in the Second Boer War | Statement: [Danie Theron Combat School, namesakeNotableFor, service in the Second Boer War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namesakeNotableFor Context triple: [Danie Theron Combat School, namesakeNotableFor, service in the Second Boer War]
-
A.
namedPersonNotableFor
Indicates that a person is especially known or recognized for a particular work, role, achievement, or characteristic.
-
B.
notableAsNamesakeOf
Indicates that one entity is recognized or distinguished specifically for being the namesake of another entity.
-
C.
fatherNotableFor
Indicates that a person's father is recognized or distinguished for a particular achievement, role, or characteristic.
-
D.
hasNamesakeNotability
chosen
Indicates that one entity is notable or recognized specifically because it shares the same name as another entity.
-
E.
sonNotableFor
Indicates that a son is recognized or distinguished for a particular achievement, role, or characteristic.
- 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_69f224d9d52c8190a61f68ded37fa755 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:10 p.m.