Triple
T36143869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Himmel Street bombing |
E1045388
|
entity |
| Predicate | filmPortrayalOfCharacterAffected |
P168523
|
FINISHED |
| Object | Liesel Meminger |
—
|
NE NERFINISHED |
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: Liesel Meminger | Statement: [Himmel Street bombing, filmPortrayalOfCharacterAffected, Liesel Meminger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmPortrayalOfCharacterAffected Context triple: [Himmel Street bombing, filmPortrayalOfCharacterAffected, Liesel Meminger]
-
A.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
-
B.
filmPortrayer
Indicates that one entity portrays or plays the role of another entity (such as a character or person) in a film.
-
C.
portraysCharacterWithDisability
Indicates that an entity depicts or represents a character who has a disability.
-
D.
filmCharacterOf
chosen
Indicates that a person or character is a character appearing in a specified film.
-
E.
isPortrayedIn
Indicates that an entity is depicted or represented within a particular work, medium, or portrayal.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.