Triple
T1452549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krupp |
E31323
|
entity |
| Predicate | benefitedFrom |
P487
|
FINISHED |
| Object | Nazi armaments programs |
—
|
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: Nazi armaments programs | Statement: [Krupp, benefitedFrom, Nazi armaments programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitedFrom Context triple: [Krupp, benefitedFrom, Nazi armaments programs]
-
A.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
benefitsCause
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or cause.
-
C.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
benefitedCountry
Indicates that one country gains an advantage, profit, or positive outcome from an action, event, or entity associated with another.
-
E.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57d34cc8190801b769d9d9b2e2e |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.