Triple
T19951843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marthinus Theunis Steyn |
E479574
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marthinus |
—
|
NE NERFINISHED |
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: Marthinus | Statement: [Marthinus Theunis Steyn, givenName, Marthinus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marthinus Context triple: [Marthinus Theunis Steyn, givenName, Marthinus]
-
A.
Marthinus
chosen
Marthinus is a masculine given name of Afrikaans and Dutch origin, historically borne by several notable South African figures.
-
B.
Roelof
Roelof is a masculine given name of Dutch origin, commonly used in the Netherlands and among Afrikaans speakers.
-
C.
Daniel François Malan
Daniel François Malan was a South African politician and prime minister best known for leading the National Party government that formally instituted apartheid in 1948.
-
D.
Wikus van de Merwe
Wikus van de Merwe is the bumbling South African bureaucrat who becomes the reluctant, transforming protagonist at the center of the sci-fi film "District 9."
-
E.
Lourens
Lourens is a given name derived from the Latin name Laurentius, commonly used in Dutch and Afrikaans contexts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a6c87388190a1bada3117acaf7b |
completed | April 20, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:54 p.m.