Triple
T6668515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 4.1 |
E151664
|
entity |
| Predicate | refinesBidirectionalAlgorithm |
P25130
|
FINISHED |
| Object | Unicode Bidirectional Algorithm |
E564766
|
NE FINISHED |
How this triple was built (3 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 Bidirectional Algorithm | Statement: [Unicode 4.1, refinesBidirectionalAlgorithm, Unicode Bidirectional Algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unicode Bidirectional Algorithm Context triple: [Unicode 4.1, refinesBidirectionalAlgorithm, Unicode Bidirectional Algorithm]
-
A.
Unicode bidirectional algorithm
chosen
The Unicode bidirectional algorithm is a core text-processing method that determines the correct display order of mixed left-to-right and right-to-left scripts, such as Latin and Arabic, in digital text.
-
B.
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.
-
C.
Unicode Line Breaking Algorithm
The Unicode Line Breaking Algorithm is a standard specification that defines how to determine valid line break opportunities in text encoded with Unicode, ensuring consistent and readable text layout across different systems and languages.
-
D.
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.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refinesBidirectionalAlgorithm Context triple: [Unicode 4.1, refinesBidirectionalAlgorithm, Unicode Bidirectional Algorithm]
-
A.
relatedAlgorithm
chosen
Indicates that one algorithm has a meaningful connection or association with another algorithm, such as similarity, dependency, or complementary function.
-
B.
refinesSupportFor
Indicates that one entity improves, clarifies, or makes more precise the support or justification provided by another entity.
-
C.
bidirectionalClass
Indicates that a class participates in a bidirectional relationship, where each related class maintains a reference to the other.
-
D.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
-
E.
alignmentWithMoreau
Indicates a relationship where an entity’s views, actions, or characteristics are in agreement or ideological conformity with those associated with Moreau.
- F. None of above.
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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef109f5c8190aa28b5d7aa192e6e |
completed | March 27, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:02 p.m.