Triple
T31463617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian Sign Language |
E802666
|
entity |
| Predicate | usesNonManualFeaturesFor |
P96851
|
FINISHED |
| Object | questions |
—
|
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: questions | Statement: [Austrian Sign Language, usesNonManualFeaturesFor, questions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNonManualFeaturesFor Context triple: [Austrian Sign Language, usesNonManualFeaturesFor, questions]
-
A.
notAutomaticallyUsedBy
Indicates that something is not used by another entity in an automatic or default manner and instead requires explicit action or configuration to be used.
-
B.
hasManual
Indicates that an entity is associated with a manual that provides instructions or documentation for it.
-
C.
hasNonManualMarkers
chosen
Indicates that a sign or gesture is accompanied by specific non-manual features (such as facial expressions, head or body movements) that contribute to its grammatical or semantic meaning.
-
D.
hasMechanicalFeature
Indicates that one entity possesses, includes, or is characterized by a specific mechanical component, attribute, or functionality.
-
E.
controlsFeaturesAt
Indicates that one entity has the authority or capability to manage, configure, or influence specific features at a particular location or context.
- 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_69f348c84c1c81908739f100ecf7394e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 9:21 p.m.