Triple
T20195879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hurricane Sessions |
E493083
|
entity |
| Predicate | capturesSoundOf |
P124232
|
FINISHED |
| Object | traditional New Orleans jazz |
—
|
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: traditional New Orleans jazz | Statement: [The Hurricane Sessions, capturesSoundOf, traditional New Orleans jazz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capturesSoundOf Context triple: [The Hurricane Sessions, capturesSoundOf, traditional New Orleans jazz]
-
A.
containsSound
chosen
Indicates that one entity includes, embodies, or produces the sound associated with another entity.
-
B.
followsSoundOf
Indicates that one entity moves or directs its attention by tracking the source or direction of a sound produced by another entity.
-
C.
hasSound
Indicates that an entity produces, emits, or is associated with a particular sound.
-
D.
hasCatchySound
Indicates that something possesses an appealing, memorable, or attractive auditory quality.
-
E.
soundCharacter
Indicates a relationship where one entity specifies the quality, style, or distinguishing characteristics of a sound produced or perceived in another entity.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad8b3cc8190aa9c9c79c552002a |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:37 p.m.