Triple
T12533494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orchestra of the Royal Opera House |
E299626
|
entity |
| Predicate | hasArtisticField |
P49761
|
FINISHED |
| Object | performing arts |
—
|
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: performing arts | Statement: [Orchestra of the Royal Opera House, hasArtisticField, performing arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtisticField Context triple: [Orchestra of the Royal Opera House, hasArtisticField, performing arts]
-
A.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
-
B.
hasArtisticGenre
Indicates that an entity (such as a work or creation) belongs to or is characterized by a particular artistic genre.
-
C.
artisticField
chosen
Indicates the artistic domain or creative discipline in which an entity is active or associated.
-
D.
hasArtisticFocus
Indicates that an entity’s primary artistic attention, theme, or specialization is directed toward a particular subject, style, or medium.
-
E.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.