Triple
T31995467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the White Swan |
E816980
|
entity |
| Predicate | hasFateInMostProductions |
P180515
|
FINISHED |
| Object | dies tragically |
—
|
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 tragically | Statement: [the White Swan, hasFateInMostProductions, dies tragically]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFateInMostProductions Context triple: [the White Swan, hasFateInMostProductions, dies tragically]
-
A.
hasFateInStory
chosen
Indicates that an entity is assigned a particular destiny, outcome, or ultimate role within the narrative of a story.
-
B.
hasNotableMultipleAppearances
Indicates that an entity appears multiple times in a context or medium in a way considered significant or noteworthy.
-
C.
hasProductionCredit
Indicates that an entity is credited as having contributed to the production of another entity, such as a work, project, or media item.
-
D.
hasOutcomeInFilm
Indicates that a particular event, action, or situation results in a specific outcome within the context of a film.
-
E.
workedAsProducerFor
Indicates that one entity served in the role of producer for a work, project, or production associated with another entity.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 1, 2026, 12:13 a.m.