Triple
T16563699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheel of Brisbane |
E402401
|
entity |
| Predicate | hasAudioCommentary |
P46114
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Wheel of Brisbane, hasAudioCommentary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAudioCommentary Context triple: [Wheel of Brisbane, hasAudioCommentary, true]
-
A.
hasCommentaryIn
Indicates that an entity is discussed, analyzed, or annotated within a specific commentary work or source.
-
B.
hasCommentaryOn
Indicates that one entity provides commentary, explanation, or evaluative remarks about another entity.
-
C.
hasCommentaryForm
Indicates that one entity exists in, or is associated with, a commentary version or format of another entity.
-
D.
hasNarration
chosen
Indicates that an entity provides spoken or written commentary or storytelling for another entity, such as a work, event, or scene.
-
E.
hasSubtitles
Indicates that one media item provides subtitle text or tracks that accompany another media item or its audio content.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3577043048190bc9bcf55069b769f |
completed | April 18, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:15 a.m.