Triple
T14318932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IDN ccTLD Fast Track |
E355029
|
entity |
| Predicate | usesScriptTypes |
P4427
|
FINISHED |
| Object | non-Latin scripts |
—
|
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: non-Latin scripts | Statement: [IDN ccTLD Fast Track, usesScriptTypes, non-Latin scripts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesScriptTypes Context triple: [IDN ccTLD Fast Track, usesScriptTypes, non-Latin scripts]
-
A.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
-
B.
appliesToScript
Indicates that something (such as a rule, configuration, or operation) is specifically relevant or applicable to a given script.
-
C.
usedInScripts
Indicates that something (such as a tool, method, or resource) is employed or referenced within one or more scripts.
-
D.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
E.
scriptType
chosen
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de883a93548190ac671b001d15d0bd |
completed | April 14, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:13 a.m.