Triple
T25597653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Wyoming v. Aaron McKinney |
E641696
|
entity |
| Predicate | crimeAdditionalAct |
P159151
|
FINISHED |
| Object | leaving victim tied to a fence |
—
|
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: leaving victim tied to a fence | Statement: [State of Wyoming v. Aaron McKinney, crimeAdditionalAct, leaving victim tied to a fence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeAdditionalAct Context triple: [State of Wyoming v. Aaron McKinney, crimeAdditionalAct, leaving victim tied to a fence]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific crime.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
E.
crimeListedInArticleIII
Indicates that a particular crime is one of the offenses expressly mentioned in Article III of the relevant constitution or legal document.
- F. None of above. chosen
Provenance (4 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_69f5f9a420f08190a8ed8c9a8c245fc4 |
completed | May 2, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 21, 2026, 4:28 p.m.