Triple
T28229646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullseye |
E711690
|
entity |
| Predicate | targetOfAssassinationPlot |
P119131
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [Bullseye, targetOfAssassinationPlot, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfAssassinationPlot Context triple: [Bullseye, targetOfAssassinationPlot, President of the United States]
-
A.
wasAssassinationTarget
chosen
Indicates that an entity was the intended victim or objective of an assassination attempt.
-
B.
assassinationOrganizedBy
Indicates that an assassination was planned, directed, or coordinated by a particular agent or organization.
-
C.
relatedAssassination
Indicates a relationship where one entity is connected to, involved in, or associated with an assassination event concerning another entity.
-
D.
wasAssassinatedIn
Indicates that an entity was killed in a deliberate, targeted assassination that occurred at a specific place or time.
-
E.
assassinatedIn
Indicates that an assassination of one entity occurred within the specified location or context represented by another entity.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 27, 2026, 10:51 p.m.