Triple
T1173237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japonic languages |
E24960
|
entity |
| Predicate | writingSystem |
P454
|
FINISHED |
| Object | Kanji |
E2128
|
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: Kanji | Statement: [Japonic languages, writingSystem, Kanji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanji Context triple: [Japonic languages, writingSystem, Kanji]
-
A.
Kanji
chosen
Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
-
B.
Hiragana
Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
-
C.
Kawi script
Kawi script is an ancient Brahmic-derived writing system historically used across Java and other parts of Southeast Asia to write Old Javanese and related languages.
-
D.
Hangul
Hangul is the native alphabetic writing system of the Korean language, renowned for its scientific design and ease of learning.
-
E.
Yapese
Yapese is an Austronesian language spoken primarily on the island of Yap and nearby islands in the western Pacific.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcecab688190b21a926874cd98d1 |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f1a13bc81909da2cfdbad397861 |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:45 p.m.