Triple
T7793335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crown Prince of Japan |
E180234
|
entity |
| Predicate | titleInKanji |
P79059
|
FINISHED |
| Object | 皇太子 |
—
|
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: 皇太子 | Statement: [Crown Prince of Japan, titleInKanji, 皇太子]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleInKanji Context triple: [Crown Prince of Japan, titleInKanji, 皇太子]
-
A.
titleInJapanese
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
B.
titleInKorean
Indicates that an entity has a specific title expressed in the Korean language.
-
C.
titleInLatinScript
Indicates that the title of an entity is written or represented using a Latin-based writing system.
-
D.
equivalentTitleInJapanese
Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
-
E.
hasTitleInRevisedRomanization
Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:31 p.m.