Triple
T749025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Speer |
E15404
|
entity |
| Predicate | defendantType |
P2238
|
FINISHED |
| Object | major war criminal |
—
|
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: major war criminal | Statement: [Albert Speer, defendantType, major war criminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defendantType Context triple: [Albert Speer, defendantType, major war criminal]
-
A.
defendant
chosen
Indicates that an entity is the party accused or sued in a legal action or proceeding.
-
B.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
C.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
D.
hasTypeOfCourt
Indicates that an entity is associated with or classified by a specific type or category of court.
-
E.
typeOfJurisdiction
Indicates the specific kind or category of legal authority or control that one jurisdiction holds in relation to a given legal or administrative context.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.