Triple
T465297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christiaan de Wet |
E8431
|
entity |
| Predicate | receivedSentence |
P14999
|
FINISHED |
| Object | term of imprisonment and fine after 1914 rebellion |
—
|
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: term of imprisonment and fine after 1914 rebellion | Statement: [Christiaan de Wet, receivedSentence, term of imprisonment and fine after 1914 rebellion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedSentence Context triple: [Christiaan de Wet, receivedSentence, term of imprisonment and fine after 1914 rebellion]
-
A.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
B.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
C.
receives
Indicates that one entity is the recipient of something (such as an object, message, or action) from another entity.
-
D.
receivedSupportFrom
Indicates that one entity obtained help, resources, or backing from another entity.
-
E.
sentenceType
Indicates the classification of a sentence according to its communicative function or structural type (e.g., question, statement, command).
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd5b6b48190ae23968135cf6417 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edea1acc81908a72d9f4c43438ea |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef611b9c8190ac5e9174744d9127 |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.