Triple
T10837184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenuzi-Dongola |
E255790
|
entity |
| Predicate | hasConsonantPhonemesApprox |
P24463
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Kenuzi-Dongola, hasConsonantPhonemesApprox, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConsonantPhonemesApprox Context triple: [Kenuzi-Dongola, hasConsonantPhonemesApprox, 20]
-
A.
hasConsonantPhonemes
chosen
Indicates that an entity possesses or includes one or more consonant phonemes in its phonological system.
-
B.
hasConsonantSigns
Indicates that one entity possesses or includes consonant sign characters as part of its representation or structure.
-
C.
hasNumberOfConsonantLetters
Indicates the relationship between an entity and the count of consonant letters present in its written form.
-
D.
hasPhonemicVowels
Indicates that a language or linguistic system distinguishes vowel sounds as separate phonemes that can change word meaning.
-
E.
hasNasalConsonants
Indicates that the subject language or word includes one or more nasal consonant sounds in its phonological inventory or pronunciation.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d746ff70148190b844ab92d796af6c |
completed | April 9, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69d70d25280c8190b648d7d1958b413a |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:19 p.m.