Triple
T30892762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justine Moritz |
E786945
|
entity |
| Predicate | indirectlyKilledBy |
P134135
|
FINISHED |
| Object | Victor Frankenstein’s creature |
—
|
NE NERFINISHED |
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: Victor Frankenstein’s creature | Statement: [Justine Moritz, indirectlyKilledBy, Victor Frankenstein’s creature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indirectlyKilledBy Context triple: [Justine Moritz, indirectlyKilledBy, Victor Frankenstein’s creature]
-
A.
killedBy
Indicates that one entity caused the death of another entity.
-
B.
killedOnBehalfOf
Indicates that one entity carried out a killing as a representative of, or in service to, another entity.
-
C.
killsOrIsKilledBy
Indicates that one entity causes the death of the other or is itself killed by that entity, capturing a mutual or directional lethal relationship between them.
-
D.
indirectFatalitiesCause
chosen
Indicates a causal relationship where an entity is responsible for deaths that occur indirectly, as a secondary or downstream consequence rather than as the immediate cause.
-
E.
allegedToHaveKilled
Indicates that one entity is claimed or accused, but not proven, to have killed 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6923826008190931f5076cd002373 |
completed | May 3, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:49 p.m.