Triple
T188950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode |
E3674
|
entity |
| Predicate | mostCommonEncodingOnWeb |
P1444
|
FINISHED |
| Object | UTF-8 |
—
|
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: UTF-8 | Statement: [Unicode, mostCommonEncodingOnWeb, UTF-8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostCommonEncodingOnWeb Context triple: [Unicode, mostCommonEncodingOnWeb, UTF-8]
-
A.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
B.
encodedIn
chosen
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
C.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
D.
secondMostSpokenLanguage
Indicates that the related language is the second most widely spoken language associated with the given entity (such as a country, region, or population).
-
E.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594abeec8190a48f36817e647fcd |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.