Triple
T24432700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camuki language |
E616041
|
entity |
| Predicate | hasVoicelessNasals |
P156118
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Camuki language, hasVoicelessNasals, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVoicelessNasals Context triple: [Camuki language, hasVoicelessNasals, yes]
-
A.
hasNasalConsonants
Indicates that the subject language or word includes one or more nasal consonant sounds in its phonological inventory or pronunciation.
-
B.
hasNasalVowels
Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
-
C.
hasVoicelessStops
Indicates that the subject language or sound system includes voiceless stop consonants (such as [p], [t], [k]) in its phonemic inventory.
-
D.
hasNasalHarmony
Indicates that a phonological process causes nasality in one segment to spread to or be shared with other segments within a word or domain.
-
E.
distinguishesVoicelessUnaspiratedConsonants
Indicates the ability to perceive or mark a difference between consonant sounds that are voiceless and unaspirated and other types of consonants.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29783b3208190997c47be1aa229af |
completed | April 29, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:16 a.m.