Triple
T11499477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swan Lake |
E272625
|
entity |
| Predicate | notableNumber |
P7729
|
FINISHED |
| Object | Swan Theme |
E235433
|
NE 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: Swan Theme | Statement: [Swan Lake, notableNumber, Swan Theme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swan Theme Context triple: [Swan Lake, notableNumber, Swan Theme]
-
A.
Swan Theme
chosen
Swan Theme is the famous recurring musical motif from Tchaikovsky’s ballet "Swan Lake," symbolizing the tragic and ethereal character of the swan princess.
-
B.
White Swan
The "White Swan" is the elegant, white Baroque-style Kaunas Town Hall in Lithuania, renowned for its slender tower and historic role as a civic landmark.
-
C.
the White Swan
The White Swan is the enchanted princess alter ego of Odette in Tchaikovsky’s ballet "Swan Lake," symbolizing purity, grace, and tragic romance.
-
D.
Big Swan
Big Swan is the popular nickname for Denka Big Swan Stadium, a large multi-purpose sports venue in Niigata, Japan, best known for hosting football matches and major events.
-
E.
Swan
Swan is a large, graceful waterbird known for its long neck, white or black plumage, and strong cultural associations with beauty and elegance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de3e9c881909d6c55334f7a832d |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e604aa9e3c8190ad86e4d05a67c8ac |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 8, 2026, 9:36 p.m.