Triple
T25597659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Wyoming v. Aaron McKinney |
E641696
|
entity |
| Predicate | victimCauseOfDeath |
P144
|
FINISHED |
| Object | severe head injuries |
—
|
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: severe head injuries | Statement: [State of Wyoming v. Aaron McKinney, victimCauseOfDeath, severe head injuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCauseOfDeath Context triple: [State of Wyoming v. Aaron McKinney, victimCauseOfDeath, severe head injuries]
-
A.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
C.
deathCharacteristic
Indicates a characteristic, attribute, or quality specifically associated with a death event or the manner in which death occurred.
-
D.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
-
E.
deathDetails
Indicates the specific circumstances, causes, and contextual information associated with an entity’s death.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 21, 2026, 4:28 p.m.