Triple
T6469938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCD |
E142321
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Unicode character property database |
E26667
|
NE 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: Unicode character property database | Statement: [UCD, alsoKnownAs, Unicode character property database]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unicode character property database Context triple: [UCD, alsoKnownAs, Unicode character property database]
-
A.
Unicode Character Database
chosen
The Unicode Character Database is a comprehensive collection of machine-readable data files that define the properties, classifications, and behaviors of every character encoded in the Unicode Standard.
-
B.
Unicode Standard code charts
Unicode Standard code charts are official visual reference tables published by the Unicode Consortium that display every encoded character, its code point, and related annotations for each script and symbol block in the Unicode Standard.
-
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 Technical Report #29
Unicode Technical Report #29 is the specification that defines how to determine and segment user-perceived text elements (grapheme clusters), words, and sentences in Unicode text.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a2e896481908ed004e3b0a33121 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6539c93c481909bed35b68ce420d8 |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:50 p.m.