Triple
T27228767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernst Schmeitzner |
E682089
|
entity |
| Predicate | employerOrPublisherOf |
P166645
|
FINISHED |
| Object | Friedrich Nietzsche |
—
|
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: Friedrich Nietzsche | Statement: [Ernst Schmeitzner, employerOrPublisherOf, Friedrich Nietzsche]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerOrPublisherOf Context triple: [Ernst Schmeitzner, employerOrPublisherOf, Friedrich Nietzsche]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
employerOrPartner
Indicates that one entity is either the employer of, or a business partner with, another entity.
-
C.
employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
-
D.
employerSide
Indicates that the subject participates in or represents the employer’s position, interests, or perspective within an employment relationship or dispute.
-
E.
employerRight
Indicates that an employer holds a specific right, entitlement, or legal authority in relation to an employee or employment situation.
- F. None of above. chosen
Provenance (4 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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f662a29b3881909957a7e3b986653c |
completed | May 2, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 27, 2026, 9:45 a.m.