Triple
T2284476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Volksgrenadier divisions |
E51354
|
entity |
| Predicate | originOfPersonnel |
P12729
|
FINISHED |
| Object | convalescents returning from hospitals |
—
|
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: convalescents returning from hospitals | Statement: [German Volksgrenadier divisions, originOfPersonnel, convalescents returning from hospitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originOfPersonnel Context triple: [German Volksgrenadier divisions, originOfPersonnel, convalescents returning from hospitals]
-
A.
personnelComposition
chosen
Indicates the makeup or distribution of people or roles within a group, organization, or unit.
-
B.
committeeOfOrigin
Indicates the committee in which a proposal, bill, or item was first introduced or initially considered.
-
C.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
-
D.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
-
E.
studentOrigin
Indicates that a student originates from, or is associated with, a particular place, institution, or source.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc2445f388190af643878145f8249 |
completed | March 7, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69abbdbb9e4c819085fc588626ec7c09 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.