Triple
T1471404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killing of Lee Harvey Oswald |
E27141
|
entity |
| Predicate | hasVictimStatus |
P20433
|
FINISHED |
| Object | accused assassin of President John F. Kennedy |
—
|
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: accused assassin of President John F. Kennedy | Statement: [Killing of Lee Harvey Oswald, hasVictimStatus, accused assassin of President John F. Kennedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVictimStatus Context triple: [Killing of Lee Harvey Oswald, hasVictimStatus, accused assassin of President John F. Kennedy]
-
A.
hasVictimCount
Indicates the number of victims associated with a particular event, action, or entity.
-
B.
hasVictimNationalities
Indicates that an event, incident, or action involved victims belonging to one or more specified nationalities.
-
C.
legalStatusOfVictims
chosen
Indicates the legal classification or condition of the victims in relation to the event or action described.
-
D.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
-
E.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5db55948190ae5262a70a161b87 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.