Triple
T22585016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode normalization |
E564765
|
entity |
| Predicate | NFKD |
P148828
|
FINISHED |
| Object | compatibility decomposition form |
—
|
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: compatibility decomposition form | Statement: [Unicode normalization, NFKD, compatibility decomposition form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NFKD Context triple: [Unicode normalization, NFKD, compatibility decomposition form]
-
A.
diacriticStrippedForm
Indicates that one textual form is derived from another by removing all diacritic marks (such as accents or umlauts) from its characters.
-
B.
standardTransliteration
Indicates that one representation of text is a transliteration of another according to a recognized standard or convention.
-
C.
usesDiacriticsFrom
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
-
D.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
E.
alternativeTransliteration
Indicates that one written form represents an alternative way of transliterating the same original text or name into another script or orthography.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615c18f88190ad4f23639d15f337 |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee626e6bb08190ada4dd8b48cc0c43 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:45 p.m.