Triple
T16704361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg IG Farben trial |
E405925
|
entity |
| Predicate | maximumSentence |
P29667
|
FINISHED |
| Object | 8 years imprisonment |
—
|
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: 8 years imprisonment | Statement: [Nuremberg IG Farben trial, maximumSentence, 8 years imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumSentence Context triple: [Nuremberg IG Farben trial, maximumSentence, 8 years imprisonment]
-
A.
sentenceLength
Indicates the length or number of units (such as characters, words, or tokens) that a given sentence contains.
-
B.
maximumSegmentLength
Indicates the greatest allowable or observed length of a segment within a given context or structure.
-
C.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
D.
maximumNumber
chosen
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
-
E.
typicalSentenceRange
Indicates the usual or most common range of sentence lengths (e.g., in years or months) typically imposed for a given offense or legal 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3833496dc8190ae4b4a03ba04d69d |
completed | April 18, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.