Triple
T13159897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Garden and Cultural Centre |
E312696
|
entity |
| Predicate | languageOfLocalContext |
P19095
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Japanese Garden and Cultural Centre, languageOfLocalContext, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalContext Context triple: [Japanese Garden and Cultural Centre, languageOfLocalContext, English]
-
A.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
B.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
-
C.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
D.
languageOfEnvironment
chosen
Indicates the language predominantly used or present in a given environment or context.
-
E.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:12 p.m.