Triple
T5328061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocaine 80s |
E123231
|
entity |
| Predicate | soundCharacteristics |
P9532
|
FINISHED |
| Object | warm analog textures |
—
|
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: warm analog textures | Statement: [Cocaine 80s, soundCharacteristics, warm analog textures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundCharacteristics Context triple: [Cocaine 80s, soundCharacteristics, warm analog textures]
-
A.
soundCharacter
Indicates a relationship where one entity specifies the quality, style, or distinguishing characteristics of a sound produced or perceived in another entity.
-
B.
speakerFeatures
Indicates that certain characteristics, attributes, or properties are associated with a speaker in a given context.
-
C.
vocalizationCharacteristic
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
D.
acousticProperty
chosen
Indicates the relationship between an entity and its sound-related characteristics, such as loudness, pitch, timbre, or other acoustic features.
-
E.
signatureSound
Indicates that something has a distinctive, characteristic sound that uniquely identifies it.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8593bd6c8190b2054e548ddf2458 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.