Triple
T2718497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California English |
E60023
|
entity |
| Predicate | prosodicFeature |
P9532
|
FINISHED |
| Object | uptalk in some younger speakers |
—
|
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: uptalk in some younger speakers | Statement: [California English, prosodicFeature, uptalk in some younger speakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prosodicFeature Context triple: [California English, prosodicFeature, uptalk in some younger speakers]
-
A.
vocalizationCharacteristic
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
B.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
C.
acousticProperty
chosen
Indicates the relationship between an entity and its sound-related characteristics, such as loudness, pitch, timbre, or other acoustic features.
-
D.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
E.
speakerFeatures
Indicates that certain characteristics, attributes, or properties are associated with a speaker in a given context.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaad577c8190819d3c641c2406f4 |
completed | March 7, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69abd8240920819087a812d816a55edb |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.