Triple
T34848275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Planetarium |
E1004530
|
entity |
| Predicate | hasBilingualSupport |
P147469
|
FINISHED |
| Object | Chinese and 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: Chinese and English | Statement: [Shanghai Planetarium, hasBilingualSupport, Chinese and English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBilingualSupport Context triple: [Shanghai Planetarium, hasBilingualSupport, Chinese and English]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
hasBilingualVersions
chosen
Indicates that something exists in two different language versions or forms.
-
C.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
D.
isMultilingual
Indicates that an entity can understand and/or communicate in multiple languages.
-
E.
usesLanguageSupport
Indicates that one entity makes use of language-related assistance, features, or services provided by another entity.
- 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4 p.m.