Triple
T74559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazi Germany |
E1491
|
entity |
| Predicate | usedCampSystem |
P4664
|
FINISHED |
| Object | concentration camps |
—
|
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: concentration camps | Statement: [Nazi Germany, usedCampSystem, concentration camps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedCampSystem Context triple: [Nazi Germany, usedCampSystem, concentration camps]
-
A.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
B.
usedSince
Indicates that an entity has been in use starting from a specified point in time and continuing thereafter.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
- F. None of above. chosen
Provenance (4 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a252201fa481908e30791954119c17 |
completed | Feb. 28, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69a24eacfdc481909e9ff99752fd42bf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2521ed5088190bbdfd22164bb4d94 |
completed | Feb. 28, 2026, 2:25 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.