Triple
T30343200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 86 -Eighty Six- |
E771808
|
entity |
| Predicate | originalTitleJapanese |
P4863
|
FINISHED |
| Object | 86-エイティシックス- |
—
|
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: 86-エイティシックス- | Statement: [86 -Eighty Six-, originalTitleJapanese, 86-エイティシックス-]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalTitleJapanese Context triple: [86 -Eighty Six-, originalTitleJapanese, 86-エイティシックス-]
-
A.
originalTitleName
Indicates that one entity is the original or primary title name associated with another entity.
-
B.
titleInJapanese
chosen
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
C.
titleInJapan
Indicates that an entity has a specific title or name when released or used in Japan.
-
D.
originalTitleOfWork
Indicates that one work is the original title under which another work was first created, published, or released.
-
E.
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.
- 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a002e71bdc48190b922f2d3b362d259 |
completed | May 10, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_6a002e1a28708190b65f9e657c770bab |
completed | May 10, 2026, 7:04 a.m. |
Created at: April 29, 2026, 7:55 p.m.