Triple
T20064648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacquetta of Luxembourg |
E499575
|
entity |
| Predicate | accusationOutcome |
P137195
|
FINISHED |
| Object | acquitted of witchcraft charges |
—
|
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: acquitted of witchcraft charges | Statement: [Jacquetta of Luxembourg, accusationOutcome, acquitted of witchcraft charges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accusationOutcome Context triple: [Jacquetta of Luxembourg, accusationOutcome, acquitted of witchcraft charges]
-
A.
resultOfAccusation
chosen
Indicates that one entity is the outcome, consequence, or product of an accusation made by another entity.
-
B.
accusationType
Indicates the specific category or nature of an accusation made by one party against another.
-
C.
outcomeForAccusers
Indicates the result or consequence experienced by the accusers as a result of a particular event, process, or decision.
-
D.
accusationContext
Indicates the situational or conversational setting in which an accusation is made, such as its background, circumstances, or framing.
-
E.
accusationDescription
Indicates that a statement or explanation is being provided that details the nature, content, or specifics of an accusation made by one party against another.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e663787190819096b2b78b38c1bf12 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:39 p.m.