Triple
T19530259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean Chinese |
E488635
|
entity |
| Predicate | bilingualCommunity |
P5562
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Korean Chinese, bilingualCommunity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bilingualCommunity Context triple: [Korean Chinese, bilingualCommunity, yes]
-
A.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
B.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
C.
bilingualismWith
Indicates a relationship where an entity possesses or is associated with the ability to use two specified languages.
-
D.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
E.
hasNeighboringLanguageCommunity
Indicates that one language community is geographically or socially adjacent to another, allowing for direct contact or interaction between them.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6363ec6cc8190b9e9ac0196b288f9 |
completed | April 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.