Triple
T22047946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bidayuhic languages |
E544809
|
entity |
| Predicate | havePhonologicalFeaturesInCommon |
P8038
|
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: [Bidayuhic languages, havePhonologicalFeaturesInCommon, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: havePhonologicalFeaturesInCommon Context triple: [Bidayuhic languages, havePhonologicalFeaturesInCommon, true]
-
A.
hasPhonologicalSimilarityTo
chosen
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
B.
hasPhonologicalBasisFor
Indicates that one entity serves as the phonological source, motivation, or foundation for another entity.
-
C.
hasDialectalFeaturesSharedWith
Indicates that two language varieties share specific dialectal features or characteristics in common.
-
D.
hasPhonologicalParameters
Indicates that an entity is associated with specific phonological features or parameters that characterize its sound structure.
-
E.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12830c674819080254d77ee02bc9f |
completed | April 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:26 p.m.