Triple
T31368840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selma Ježková |
E800089
|
entity |
| Predicate | fantasizesThrough |
P69553
|
FINISHED |
| Object | musical numbers |
—
|
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: musical numbers | Statement: [Selma Ježková, fantasizesThrough, musical numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fantasizesThrough Context triple: [Selma Ježková, fantasizesThrough, musical numbers]
-
A.
hypnotizes
Indicates inducing an altered mental state in another entity, typically causing heightened suggestibility or trance-like focus.
-
B.
enchantedTo
Indicates that one entity has been magically imbued or altered so that it possesses a special effect, property, or behavior caused by another entity.
-
C.
chanted
Indicates that an entity vocalized rhythmic or repetitive words or sounds, often in unison or with a steady cadence, directed toward another entity or in a particular context.
-
D.
dream
chosen
Indicates that an entity experiences or has a dream involving another entity or concept.
-
E.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
- 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_69f224e6b7448190ac6bf97ad7364160 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f88006c81909440631225f38c04 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:18 p.m.