Triple
T11213186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōgō |
E265360
|
entity |
| Predicate | hasEnglishGloss |
P97872
|
FINISHED |
| Object | empress consort |
—
|
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: empress consort | Statement: [Kōgō, hasEnglishGloss, empress consort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishGloss Context triple: [Kōgō, hasEnglishGloss, empress consort]
-
A.
hasMultilingualGlosses
Indicates that an entity is associated with glosses or explanatory labels available in multiple languages.
-
B.
hasGlossesBy
Indicates a relationship where one entity provides or is associated with explanatory glosses or definitions for another entity.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasEnglishNameMeaning
Indicates that an entity is associated with an English-language name along with the meaning or semantic interpretation of that name.
-
E.
etymologyGloss
Indicates that a term’s meaning is explained by a brief gloss specifically describing its etymological origin or source.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d7f47c8190b78c640ff1a01943 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.