Triple
T457464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stalags |
E7263
|
entity |
| Predicate | hadSubcamps |
P747
|
FINISHED |
| Object | Arbeitskommandos (labor detachments) |
—
|
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: Arbeitskommandos (labor detachments) | Statement: [Stalags, hadSubcamps, Arbeitskommandos (labor detachments)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSubcamps Context triple: [Stalags, hadSubcamps, Arbeitskommandos (labor detachments)]
-
A.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
B.
hasCampType
Indicates that an entity is associated with or classified by a particular type or category of camp.
-
C.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
D.
hasSubcommunityIn
Indicates that a larger community contains or encompasses a smaller, distinct subcommunity located within it.
-
E.
hadFort
Indicates that an entity possessed, controlled, or contained a fort at some time.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa1616481909399f92551a0c9e3 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede614b88190be07425f5535f56d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.