Triple
T11829797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warao language |
E281355
|
entity |
| Predicate | hasNasals |
P76257
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Warao language, hasNasals, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNasals Context triple: [Warao language, hasNasals, true]
-
A.
hasNasalConsonants
chosen
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.
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.
-
D.
distinguishesSyllabicNasals
Indicates that a language or system makes a phonological distinction between syllabic nasal consonants and other types of segments.
-
E.
hasConsonantHarmony
Indicates that the entities are related by a pattern where consonants within a linguistic unit adjust to share similar features, creating consonant harmony.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62b75dc8190b27d24e46a262a11 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.