Triple
T2119775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swan Lake |
E43891
|
entity |
| Predicate | keyFeatures |
P7153
|
FINISHED |
| Object | leitmotifs associated with characters |
—
|
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: leitmotifs associated with characters | Statement: [Swan Lake, keyFeatures, leitmotifs associated with characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyFeatures Context triple: [Swan Lake, keyFeatures, leitmotifs associated with characters]
-
A.
keyFeature
chosen
Indicates that something is a primary, distinguishing, or most important feature of an entity.
-
B.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
C.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
D.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
E.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
- 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.