Triple
T32590776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claudia Tiedemann |
E833056
|
entity |
| Predicate | hasYoungVersionPortrayedBy |
P39940
|
FINISHED |
| Object | Gwendolyn Göbel |
—
|
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: Gwendolyn Göbel | Statement: [Claudia Tiedemann, hasYoungVersionPortrayedBy, Gwendolyn Göbel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYoungVersionPortrayedBy Context triple: [Claudia Tiedemann, hasYoungVersionPortrayedBy, Gwendolyn Göbel]
-
A.
youngerVersionPortrayedBy
chosen
Indicates that one person portrays a younger version of another person, typically in a film, television show, or similar narrative work.
-
B.
portraysYoungerVersionOfCharacterFrom
Indicates that one character is depicted as a younger version of another character from a specified source.
-
C.
hasYoungPortrayalOf
Indicates that one entity is a portrayal or depiction of another entity specifically in their younger age or earlier life stage.
-
D.
portrayedAsAdultBy
Indicates that one entity is depicted or represented as an adult by another entity (such as an artist, author, or creator).
-
E.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c690ad9c8190b81204f8bf7adff0 |
completed | May 3, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:05 a.m.