Triple
T6496133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balinese language |
E148164
|
entity |
| Predicate | hasSpeechLevels |
P71062
|
FINISHED |
| Object | low speech level |
—
|
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: low speech level | Statement: [Balinese language, hasSpeechLevels, low speech level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeechLevels Context triple: [Balinese language, hasSpeechLevels, low speech level]
-
A.
hasSpeech
Indicates that an entity produces, delivers, or is associated with a spoken utterance or verbal expression.
-
B.
haveRichVoiceSystem
Indicates that an entity possesses a voice system characterized by richness, such as depth, fullness, or expressive quality.
-
C.
hasVoiceSystem
Indicates that one entity possesses or is equipped with a particular voice-based system or voice technology.
-
D.
speakerConfiguration
Indicates how speakers are arranged or assigned within an audio or communication setup.
-
E.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
- F. None of above. chosen
Provenance (4 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab958808190bd85e007e925ffc4 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:53 p.m.