Triple
T757314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erla Maschinenwerk |
E15584
|
entity |
| Predicate | usedLaborType |
P3027
|
FINISHED |
| Object | forced labor |
—
|
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: forced labor | Statement: [Erla Maschinenwerk, usedLaborType, forced labor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLaborType Context triple: [Erla Maschinenwerk, usedLaborType, forced labor]
-
A.
usedInWork
Indicates that something (such as a concept, method, material, or component) is employed or applied within a particular work, project, or creation.
-
B.
laborSystem
chosen
Indicates the type or structure of work organization, employment arrangements, and labor relations that govern how work is performed and managed.
-
C.
laborProvision
Indicates the provision or supply of labor or workforce from one party to another for work or services.
-
D.
typeOfWork
Indicates the kind or category of work associated with or performed by an entity.
-
E.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66ab4608190afcd81e6606c5116 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.