Triple
T186021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assassination of Abraham Lincoln |
E3981
|
entity |
| Predicate | BoothOccupation |
P2374
|
FINISHED |
| Object | stage actor |
—
|
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: stage actor | Statement: [Assassination of Abraham Lincoln, BoothOccupation, stage actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BoothOccupation Context triple: [Assassination of Abraham Lincoln, BoothOccupation, stage actor]
-
A.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
sponsorOccupation
Indicates that one entity serves as the occupation or professional role of a sponsor associated with another entity.
-
C.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
D.
victimOccupation
Indicates the profession or job role held by the person who is the victim in an event or incident.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.