Triple
T607928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen-Belsen |
E12033
|
entity |
| Predicate | campType |
P10334
|
FINISHED |
| Object | detention 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: detention camp | Statement: [Bergen-Belsen, campType, detention camp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campType Context triple: [Bergen-Belsen, campType, detention camp]
-
A.
trainingCampSite
Indicates that a location serves as the site where training camps are held or conducted.
-
B.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
C.
parkType
Indicates the specific category or classification of a park based on its designated use, management, or characteristics.
-
D.
notableCamp
Indicates that an entity is a camp that is notable or significant in some recognized way (e.g., historically, culturally, or by prominence).
-
E.
hasCampType
chosen
Indicates that an entity is associated with or classified by a particular type or category of camp.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.