Triple
T26971070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gräbschen |
E679318
|
entity |
| Predicate | beforeYear |
P126477
|
FINISHED |
| Object | 1945 part of Germany |
—
|
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: 1945 part of Germany | Statement: [Gräbschen, beforeYear, 1945 part of Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beforeYear Context triple: [Gräbschen, beforeYear, 1945 part of Germany]
-
A.
optionalYearBefore
Indicates that one entity may, but does not necessarily, occur or be valid in a year that precedes the year associated with another entity.
-
B.
previousEventYear
chosen
Indicates that one event occurred in a year that is earlier than the year of another event.
-
C.
previousPeriod
Indicates that one time period directly precedes another in a sequence of periods.
-
D.
chronologyPreviousYear
Indicates that one time-related entity occurs exactly one calendar year before another in a chronological sequence.
-
E.
pastSettingYear
Indicates that an event, narrative, or situation is set in or associated with a specific year in the past.
- 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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62124ff1081908d66c2ff35ba5e89 |
completed | May 2, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:39 a.m.