Triple
T25854199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyat Pree |
E651295
|
entity |
| Predicate | adaptationDifferenceFromBook |
P152697
|
FINISHED |
| Object | dies in Season 2 of the TV series |
—
|
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: dies in Season 2 of the TV series | Statement: [Pyat Pree, adaptationDifferenceFromBook, dies in Season 2 of the TV series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationDifferenceFromBook Context triple: [Pyat Pree, adaptationDifferenceFromBook, dies in Season 2 of the TV series]
-
A.
adaptationDifferenceFromBooks
chosen
Indicates a difference between how something is portrayed in an adaptation and how it appears in the original books.
-
B.
adaptationDifference
Indicates a difference or change in how two entities adapt or have adapted relative to each other.
-
C.
adaptedBook
Indicates that a book has been transformed or reworked from an original source, such as another medium, edition, or context.
-
D.
notableDifferenceFromDisneyAdaptation
Indicates that something differs in a significant way from how it is portrayed in a Disney adaptation.
-
E.
adaptationOfFirstNovel
Indicates that the subject work is an adaptation specifically of the first novel in a given series or by a particular author.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60c698ae48190871cd445422bad91 |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 22, 2026, 7:59 a.m.