Triple
T22809730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staatsratsvorsitzender |
E564639
|
entity |
| Predicate | Einführung |
P83636
|
FINISHED |
| Object | 1960 |
—
|
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: 1960 | Statement: [Staatsratsvorsitzender, Einführung, 1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Einführung Context triple: [Staatsratsvorsitzender, Einführung, 1960]
-
A.
introductionContext
Indicates the situational or background circumstances under which an introduction between entities takes place.
-
B.
hasIntroduction
Indicates that one entity includes or provides an introductory section, part, or presentation for another entity.
-
C.
sectionIntroduced
chosen
Indicates that a particular section was introduced or added at a specific point in time or context.
-
D.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
E.
hasIntro
Indicates that an entity includes or is associated with an introductory section or opening part.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5f1f348190a35e87939732c99f |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:32 p.m.