Triple
T1498267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flick Trial |
E29735
|
entity |
| Predicate | sentenceOfFriedrichFlick |
P28514
|
FINISHED |
| Object | 7 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: 7 years imprisonment | Statement: [Flick Trial, sentenceOfFriedrichFlick, 7 years imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceOfFriedrichFlick Context triple: [Flick Trial, sentenceOfFriedrichFlick, 7 years imprisonment]
-
A.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
B.
FrederickAssessment
Indicates that an entity (typically Frederick) performs, records, or is associated with an evaluation or assessment of another entity or situation.
-
C.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
D.
associatedWithFamousSlogan
Indicates that an entity is connected to, known for, or commonly linked with a particular famous slogan.
-
E.
pilotSentence
Indicates that an entity operates or controls an aircraft or similar vehicle in the context of a described situation or sentence.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6ef5ce88190a6b520525a6d42a3 |
completed | March 1, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69a4c48a8cf48190a6ebf8d44a608a06 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c4feea448190b2b5071b28a5b608 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8:12 p.m.