Triple
T10809559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Baylock |
E255059
|
entity |
| Predicate | killsOrAttemptsToKill |
P59012
|
FINISHED |
| Object | those who threaten Damien |
—
|
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: those who threaten Damien | Statement: [Mrs. Baylock, killsOrAttemptsToKill, those who threaten Damien]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killsOrAttemptsToKill Context triple: [Mrs. Baylock, killsOrAttemptsToKill, those who threaten Damien]
-
A.
canKill
Indicates that one entity has the ability or potential to cause the death of another entity.
-
B.
kills
Indicates that one entity causes the death of another entity, ending its life.
-
C.
killsByProxy
Indicates that one entity causes the death of another entity indirectly through an intermediary or agent rather than committing the act personally.
-
D.
attemptedToKill
chosen
Indicates that one entity took deliberate action with the intention of causing the death of another entity, regardless of whether the death actually occurred.
-
E.
considersKilling
Indicates that one entity is contemplating or evaluating the possibility of killing 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b6efc48190bb64b5a8fac843c4 |
completed | April 9, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.