Triple
T1690245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Article 47 of the Constitution of Japan |
E36534
|
entity |
| Predicate | hasJapaneseText |
P31360
|
FINISHED |
| Object | 両議院の議員の選挙については、法律でこれを定める。 |
—
|
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: 両議院の議員の選挙については、法律でこれを定める。 | Statement: [Article 47 of the Constitution of Japan, hasJapaneseText, 両議院の議員の選挙については、法律でこれを定める。]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJapaneseText Context triple: [Article 47 of the Constitution of Japan, hasJapaneseText, 両議院の議員の選挙については、法律でこれを定める。]
-
A.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
B.
usesKatakanaFor
Indicates that one entity is written or represented using katakana script in relation to another entity.
-
C.
hasOfficialNameInJapanese
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
-
D.
usesKanjiFrom
Indicates that one writing system, word, or text incorporates or is composed of kanji characters originating from another specified source.
-
E.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69aa61b71cec8190b273588051058ebd |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aaf33347e48190a32b6d0099e3d389 |
completed | March 6, 2026, 3:30 p.m. |
Created at: March 4, 2026, 7:29 p.m.