Triple
T29894121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Serious Game |
E759230
|
entity |
| Predicate | hasAdaptationOfSameNovel |
P182763
|
FINISHED |
| Object | The Serious Game (1945 film) |
—
|
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: The Serious Game (1945 film) | Statement: [A Serious Game, hasAdaptationOfSameNovel, The Serious Game (1945 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdaptationOfSameNovel Context triple: [A Serious Game, hasAdaptationOfSameNovel, The Serious Game (1945 film)]
-
A.
isAdaptationOfSecondNovel
Indicates that one work is an adaptation specifically of the second novel in a series or sequence.
-
B.
isAdaptationOfThirdNovel
Indicates that one work is an adaptation specifically of the third novel in a particular series or sequence.
-
C.
adaptationOfFirstNovel
Indicates that the subject work is an adaptation specifically of the first novel in a given series or by a particular author.
-
D.
hasNovelization
Indicates that a work has been adapted into a novel or prose narrative form.
-
E.
associatedWithAuthorOfSourceNovel
Indicates a relationship where one entity is connected or linked in some way to the author of the original source novel.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7908ec35881909a42f954fb9fa16e |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78fd3fd888190b7db0b563f298585 |
completed | May 3, 2026, 6:11 p.m. |
Created at: April 29, 2026, 6:03 p.m.