Triple
T32154086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Preppy Killer |
E821232
|
entity |
| Predicate | hasVictimFullName |
P69836
|
FINISHED |
| Object | Jennifer Dawn Levin |
—
|
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: Jennifer Dawn Levin | Statement: [Preppy Killer, hasVictimFullName, Jennifer Dawn Levin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVictimFullName Context triple: [Preppy Killer, hasVictimFullName, Jennifer Dawn Levin]
-
A.
victimFullName
chosen
Indicates the complete personal name of the individual who is the victim in the described event or relationship.
-
B.
hasMainVictim
Indicates that an event, action, or harmful situation primarily targets or affects a specific victim as its main subject.
-
C.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
D.
hasVictims
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
-
E.
perpetratorFullName
Indicates the complete personal name of the individual who committed or is responsible for the act or offense.
- 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 1, 2026, 12:32 a.m.