Triple
T833865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church Street Cemetery, Pretoria |
E18026
|
entity |
| Predicate | hasGravesFrom |
P20173
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Church Street Cemetery, Pretoria, hasGravesFrom, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGravesFrom Context triple: [Church Street Cemetery, Pretoria, hasGravesFrom, 19th century]
-
A.
hasTypeOfBurial
Indicates the specific kind or method of burial associated with an entity.
-
B.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
-
C.
hasGravestoneStyle
Indicates that an entity’s gravestone is characterized by or associated with a particular style or design.
-
D.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
E.
hasCemetery
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb84fe081909b8f4b4202845860 |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7b3d2481909199f7c9f305bdfe |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab60fea8819098ce3269181897d1 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.