Triple
T2484505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chichewa |
E55892
|
entity |
| Predicate | hasTonalPhonology |
P12025
|
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: [Chichewa, hasTonalPhonology, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTonalPhonology Context triple: [Chichewa, hasTonalPhonology, yes]
-
A.
hasPhonemicTone
chosen
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
B.
hasOwnPhonology
Indicates that an entity possesses its own distinct phonological system or set of sound patterns, separate from those of other entities.
-
C.
hasPhonemicVowels
Indicates that a language or linguistic system distinguishes vowel sounds as separate phonemes that can change word meaning.
-
D.
hasVowelHarmony
Indicates that the phonological vowels in a word or morpheme conform to a systematic harmony pattern (e.g., all front or all back vowels) according to the language’s vowel harmony rules.
-
E.
hasNasalVowels
Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.