Triple
T29754664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meʼphaa languages |
E752996
|
entity |
| Predicate | haveToneDistinguishingLexicalMeaning |
P12025
|
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: [Meʼphaa languages, haveToneDistinguishingLexicalMeaning, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveToneDistinguishingLexicalMeaning Context triple: [Meʼphaa languages, haveToneDistinguishingLexicalMeaning, true]
-
A.
hasDistinctLetterForSound
Indicates that a particular sound is represented by its own unique letter, distinct from other sounds in the writing system.
-
B.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
C.
hasPhonemicTone
chosen
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
D.
hasDialectalDifferenceWith
Indicates that two language varieties differ from each other in dialectal features such as pronunciation, vocabulary, or grammar.
-
E.
hasPhonologicalBasisFor
Indicates that one entity serves as the phonological source, motivation, or foundation for another entity.
- 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f673c9d2a88190965075607fc73061 |
completed | May 2, 2026, 9:59 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:56 p.m.