Triple
T20178894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uno |
E492671
|
entity |
| Predicate | languageDependency |
P138982
|
FINISHED |
| Object | no text on number cards |
—
|
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: no text on number cards | Statement: [Uno, languageDependency, no text on number cards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageDependency Context triple: [Uno, languageDependency, no text on number cards]
-
A.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
B.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
C.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
D.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
E.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
- F. None of above. chosen
Provenance (4 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668ed07c8819091bd9ffda237a91c |
completed | April 20, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:36 p.m.