Triple
T15710683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Berg |
E380828
|
entity |
| Predicate | characterInPeriod |
P119878
|
FINISHED |
| Object | post-World War II 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: post-World War II Germany | Statement: [Michael Berg, characterInPeriod, post-World War II Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInPeriod Context triple: [Michael Berg, characterInPeriod, post-World War II Germany]
-
A.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
B.
characterCreatedInYear
Indicates the specific calendar year in which a fictional or narrative character was first created or introduced.
-
C.
characterInPlayBy
Indicates that a character appears in or is part of a play authored or created by a specific person.
-
D.
characterPortrayedInYear
Indicates that a particular character was portrayed in a specific year.
-
E.
characterPerformer
Indicates that a performer portrays or voices a particular character in a work.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0094af5b481908ad51d5d7ba0c726 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 4:45 a.m.