Triple
T1431831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minahasan languages |
E30463
|
entity |
| Predicate | havePhonologicalFeature |
P7162
|
FINISHED |
| Object | rich consonant inventory |
—
|
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: rich consonant inventory | Statement: [Minahasan languages, havePhonologicalFeature, rich consonant inventory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: havePhonologicalFeature Context triple: [Minahasan languages, havePhonologicalFeature, rich consonant inventory]
-
A.
hasPhonologicalType
Indicates that one entity is characterized by or classified as having a particular phonological type (e.g., in terms of sound structure or phonological category).
-
B.
hasPhoneme
Indicates that a linguistic unit (such as a word or morpheme) contains or includes a particular phoneme as part of its sound structure.
-
C.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
-
D.
hasLinguisticFeature
chosen
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
E.
hasVowelFeature
Indicates that an entity possesses a specific vowel-related phonological or articulatory feature.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69a4c4771c9481908ae47c959debbe77 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.