Triple
T4576522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .台湾 |
E123151
|
entity |
| Predicate | punycodeForm |
P27639
|
FINISHED |
| Object | .xn--kpry57d |
—
|
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: .xn--kpry57d | Statement: [.台湾, punycodeForm, .xn--kpry57d]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: punycodeForm Context triple: [.台湾, punycodeForm, .xn--kpry57d]
-
A.
punycodeSupport
Indicates whether a system or component supports encoding and decoding Unicode text using the Punycode representation.
-
B.
punycodeIDNExample
chosen
Indicates that the example demonstrates how an internationalized domain name (IDN) is represented or encoded using Punycode.
-
C.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
-
D.
usesPhoneticSystem
Indicates that one entity employs or is based on a particular phonetic system for representing or encoding sounds.
-
E.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58dfe3508190b21836079e951a3c |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.