Triple
T34258719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 九十九里浜 |
E878965
|
entity |
| Predicate | 文化的側面 |
P14191
|
FINISHED |
| Object | 文学作品や歌謡曲の題材になっている |
—
|
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: 文学作品や歌謡曲の題材になっている | Statement: [九十九里浜, 文化的側面, 文学作品や歌謡曲の題材になっている]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 文化的側面 Context triple: [九十九里浜, 文化的側面, 文学作品や歌謡曲の題材になっている]
-
A.
culturalSphere
chosen
Indicates that one entity belongs to, is influenced by, or participates in the cultural domain, tradition, or milieu defined by another entity.
-
B.
culturalType
Indicates the classification of something according to its cultural category, style, or tradition.
-
C.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
D.
culturalLayer
Indicates the relationship in which something belongs to, originates from, or is associated with a particular cultural stratum, tradition, or level within a culture.
-
E.
culturalSector
Indicates a relationship where something is part of, associated with, or operates within a specific cultural sector or domain.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.