Triple
T7874927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Kipps |
E182825
|
entity |
| Predicate | suffersConsequenceOfCurse |
P812
|
FINISHED |
| Object | death of his wife |
—
|
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: death of his wife | Statement: [Arthur Kipps, suffersConsequenceOfCurse, death of his wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suffersConsequenceOfCurse Context triple: [Arthur Kipps, suffersConsequenceOfCurse, death of his wife]
-
A.
associatedCurse
Indicates that one entity is linked to, affected by, or bears responsibility for a particular curse related to another entity.
-
B.
attemptedCurseReversal
Indicates an action where one entity tried, but did not necessarily succeed, to reverse or undo a curse affecting another entity.
-
C.
scripturalCurse
Indicates that one entity pronounces or embodies a curse upon another as recorded or prescribed in a religious or scriptural context.
-
D.
sleepCurse
Indicates a condition where one entity has magically imposed or is affected by a curse that causes unnatural or enforced sleep.
-
E.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a961188190b2f12f8fe5d66641 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:56 p.m.