Triple
T22481670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 5.0 |
E555779
|
entity |
| Predicate | defines |
P264
|
FINISHED |
| Object | Unicode normalization forms |
—
|
NE NERFINISHED |
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: Unicode normalization forms | Statement: [Unicode 5.0, defines, Unicode normalization forms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unicode normalization forms Context triple: [Unicode 5.0, defines, Unicode normalization forms]
-
A.
Unicode normalization
chosen
Unicode normalization is a set of standardized processes that convert equivalent Unicode text sequences into a consistent canonical form to ensure reliable comparison, searching, and processing of text across systems.
-
B.
Unicode Standard
The Unicode Standard is a universal character encoding system that assigns unique code points to text and symbols from virtually all writing systems, enabling consistent digital representation and interchange of text worldwide.
-
C.
Unicode Technical Standard #35
Unicode Technical Standard #35 is a Unicode Consortium specification that defines the Locale Data Markup Language (LDML) and related mechanisms for internationalization, including formatting of dates, times, numbers, and other locale-sensitive data.
-
D.
Unicode Technical Standard #10
Unicode Technical Standard #10 is the specification that defines the Unicode Collation Algorithm, providing a standardized method for comparing and sorting Unicode text across languages and platforms.
-
E.
Unicode text processing algorithms
Unicode text processing algorithms are standardized procedures that define how Unicode text is compared, sorted, segmented, normalized, and otherwise manipulated consistently across different systems and languages.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c397b248190b36c2fbfa6489693 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.