Triple
T1035441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Parris |
E22350
|
entity |
| Predicate | causeOfEvent |
P694
|
FINISHED |
| Object | her reported fits and afflictions helped spark witchcraft accusations |
—
|
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: her reported fits and afflictions helped spark witchcraft accusations | Statement: [Elizabeth Parris, causeOfEvent, her reported fits and afflictions helped spark witchcraft accusations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfEvent Context triple: [Elizabeth Parris, causeOfEvent, her reported fits and afflictions helped spark witchcraft accusations]
-
A.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
reasonForEvent
Indicates that one event occurs as a consequence of, or is motivated or explained by, another specified cause or reason.
-
C.
causeSupported
Indicates that an entity provides backing, endorsement, or assistance to a particular cause or initiative.
-
D.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
E.
debatedAsCauseOf
Indicates that one entity is discussed or argued over as a possible cause or origin of another entity.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d669448190955507e2e4975b9f |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b728ad3481909cf1430349cb9bba |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.