Triple
T33547485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Emeritus of Japan |
E859243
|
entity |
| Predicate | hasAlternativeJapaneseTitle |
P57913
|
FINISHED |
| Object | 太上天皇 |
—
|
NE NERFINISHED |
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: 太上天皇 | Statement: [Emperor Emeritus of Japan, hasAlternativeJapaneseTitle, 太上天皇]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeJapaneseTitle Context triple: [Emperor Emeritus of Japan, hasAlternativeJapaneseTitle, 太上天皇]
-
A.
hasAlternateTitleRegion
Indicates that an entity has an alternate title that is specifically used or valid within a particular geographic region.
-
B.
haveAlternativeTitle
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
C.
hasAlternativeEditionTitle
Indicates that an entity has a different or variant title used in another edition of the same work.
-
D.
languageOfAlternativeTitle
Indicates the language in which an alternative or variant title of an entity is expressed.
-
E.
equivalentTitleInJapanese
chosen
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.
- 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: May 1, 2026, 1:39 a.m.