Triple
T18092371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of New Jersey v. John Artis |
E433002
|
entity |
| Predicate | victimCountDescription |
P74879
|
FINISHED |
| Object | triple homicide |
—
|
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: triple homicide | Statement: [State of New Jersey v. John Artis, victimCountDescription, triple homicide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCountDescription Context triple: [State of New Jersey v. John Artis, victimCountDescription, triple homicide]
-
A.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
B.
numberOfVictimsClaimed
chosen
Indicates the reported count of victims associated with a particular event, incident, or action.
-
C.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
D.
victimCountPolicy
Indicates the rule or criterion used to determine how victims are counted or classified in a given context.
-
E.
mainVictims
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd1972a881908072990de0715547 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.