Triple
T31463986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican Sign Language |
E802674
|
entity |
| Predicate | usesClassifierConstructions |
P48601
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mexican Sign Language, usesClassifierConstructions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesClassifierConstructions Context triple: [Mexican Sign Language, usesClassifierConstructions, yes]
-
A.
usesClassifiers
chosen
Indicates that one entity employs or relies on a system of classifiers (such as category labels or measure words) when referring to or organizing another entity.
-
B.
usesClassificationCriteria
Indicates that one entity applies specific classification criteria to categorize, organize, or evaluate another entity.
-
C.
usedToClassify
Indicates that one entity serves as a criterion or basis for categorizing or grouping another entity.
-
D.
usesClass
Indicates that one entity makes use of, depends on, or is implemented using a particular class in its structure or behavior.
-
E.
supportsClassification
Indicates that one entity provides the capability or functionality needed for another entity to perform or maintain a specific classification.
- 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_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: April 30, 2026, 9:22 p.m.