Triple
T3641871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gustloff-Werk II subcamp |
E77205
|
entity |
| Predicate | hasTypeOfCamp |
P10334
|
FINISHED |
| Object | labor camp |
—
|
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: labor camp | Statement: [Gustloff-Werk II subcamp, hasTypeOfCamp, labor camp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfCamp Context triple: [Gustloff-Werk II subcamp, hasTypeOfCamp, labor camp]
-
A.
hasCampType
chosen
Indicates that an entity is associated with or classified by a particular type or category of camp.
-
B.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
C.
hasResortType
Indicates that an entity (such as a resort or accommodation) is associated with a specific category or type of resort (e.g., beach resort, ski resort, spa resort).
-
D.
hadCamp
Indicates that an entity conducted, hosted, or participated in a camp event or camping activity.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc359a91481908aef1c022f45e55c |
completed | March 8, 2026, 6:43 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.