Triple
T23791817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | That's Livin' Alright |
E588111
|
entity |
| Predicate | televisionSeriesTitleOfThemeSeries |
P153585
|
FINISHED |
| Object | Auf Wiedersehen, Pet |
—
|
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: Auf Wiedersehen, Pet | Statement: [That's Livin' Alright, televisionSeriesTitleOfThemeSeries, Auf Wiedersehen, Pet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionSeriesTitleOfThemeSeries Context triple: [That's Livin' Alright, televisionSeriesTitleOfThemeSeries, Auf Wiedersehen, Pet]
-
A.
inSeriesTheme
Indicates that one entity serves as the thematic subject or focus within a particular series.
-
B.
televisionSpecialTitle
Indicates the title assigned to a specific television special in which the subject is involved or featured.
-
C.
EnglishSeriesTitle
Indicates the title by which a series is known in the English language.
-
D.
isTitleSeriesOf
Indicates that one entity is the title or name associated with a particular series (such as a book, film, or media franchise).
-
E.
episodeTitle
Indicates that a given title string is the name of a specific episode within a series or program.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c6d8215c8190af4f2dd7478e2c04 |
completed | April 29, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:17 p.m.