Triple
T838880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mori |
E18131
|
entity |
| Predicate | nameOrderInJapan |
P20511
|
FINISHED |
| Object | placed before given name |
—
|
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: placed before given name | Statement: [Mori, nameOrderInJapan, placed before given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameOrderInJapan Context triple: [Mori, nameOrderInJapan, placed before given name]
-
A.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
B.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
-
C.
eraNumberInJapan
Indicates the specific numbered position of a historical era within the sequence of Japanese eras.
-
D.
hasOfficialNameInJapanese
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
-
E.
usesKatakanaFor
Indicates that one entity is written or represented using katakana script in relation to another entity.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe4ab1081909207ae2eec1898d9 |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7dfc5c8190890c9df485d73a86 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4893e481908632102d240466dc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.