Triple
T11976822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prioress's Tale |
E285060
|
entity |
| Predicate | featuresViolenceAgainst |
P51439
|
FINISHED |
| Object | Jews against a Christian child |
—
|
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: Jews against a Christian child | Statement: [The Prioress's Tale, featuresViolenceAgainst, Jews against a Christian child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresViolenceAgainst Context triple: [The Prioress's Tale, featuresViolenceAgainst, Jews against a Christian child]
-
A.
usedViolenceAgainst
chosen
Indicates that one entity intentionally inflicted physical force or harm upon another entity.
-
B.
hasTypeOfViolence
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
C.
positionOnViolence
Indicates a stance, attitude, or policy that an entity holds regarding the use, justification, or acceptability of violence.
-
D.
viewOnViolence
Indicates an entity’s stance, opinion, or attitude toward the use of violence.
-
E.
containsGraphicViolence
Indicates that the subject includes depictions of explicit, intense, or realistic physical harm or brutality.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.