Triple
T11309884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 意賀美神社 |
E267808
|
entity |
| Predicate | 言語圏 |
P29819
|
FINISHED |
| Object | 日本語圏 |
—
|
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: 日本語圏 | Statement: [意賀美神社, 言語圏, 日本語圏]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 言語圏 Context triple: [意賀美神社, 言語圏, 日本語圏]
-
A.
linguisticArea
Indicates a regional context in which languages share features due to geographic proximity and contact rather than common genetic origin.
-
B.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
C.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
D.
ethnoLinguisticRegionOf
Indicates that a region is defined or characterized by the shared ethnic and linguistic identity of the group associated with it.
-
E.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.