Triple
T2119784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swan Lake |
E43891
|
entity |
| Predicate | hasAlternativeEnding |
P21136
|
FINISHED |
| Object | tragic ending (death of Odette and Siegfried) |
—
|
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: tragic ending (death of Odette and Siegfried) | Statement: [Swan Lake, hasAlternativeEnding, tragic ending (death of Odette and Siegfried)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeEnding Context triple: [Swan Lake, hasAlternativeEnding, tragic ending (death of Odette and Siegfried)]
-
A.
hasConditionalEnding
Indicates that one entity concludes or terminates only if a specified condition involving another entity is met.
-
B.
hasTragicEnding
chosen
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
C.
hasEnding
Indicates that one entity concludes with, or terminates in, another entity (such as a specific substring, segment, or final component).
-
D.
endedWith
Indicates that one event, process, or state concluded with or was finalized by another specified event, condition, or outcome.
-
E.
alternateTimelineName
Indicates that one entity is the name or designation used for another entity in an alternate or parallel timeline.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb32efb48190bcb99f30787a3a55 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.