Triple
T7593005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 太郎 |
E179784
|
entity |
| Predicate | syllabarySpelling |
P78042
|
FINISHED |
| Object | たろう |
—
|
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: たろう | Statement: [太郎, syllabarySpelling, たろう]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: syllabarySpelling Context triple: [太郎, syllabarySpelling, たろう]
-
A.
syllabaryDevelopedBy
Indicates that a particular syllabary was created, devised, or developed by a specific agent (such as a person, group, or culture).
-
B.
hasSyllabary
Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
-
C.
usesFixedSpellingsForCommonSyllables
Indicates that an entity consistently applies predetermined, standard spellings for frequently occurring syllables.
-
D.
usesSyllables
Indicates that one entity forms, expresses, or analyzes something by employing syllables as its basic units.
-
E.
spellingStability
Indicates the degree to which the spelling of a word or term remains consistent over time or across different uses.
- 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9b92c348190b547f0aacfb8d6be |
completed | March 27, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e2e42c8190afc802c4796c9cc2 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:53 p.m.