Triple
T6550820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malay weddings |
E151123
|
entity |
| Predicate | coreLanguageUsed |
P58450
|
FINISHED |
| Object | Malay language |
—
|
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: Malay language | Statement: [Malay weddings, coreLanguageUsed, Malay language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreLanguageUsed Context triple: [Malay weddings, coreLanguageUsed, Malay language]
-
A.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
B.
languagesUsed
chosen
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
C.
languageDiscussedIn
Indicates that a particular language is the topic of discussion within a specified context, source, or discourse.
-
D.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
E.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:51 p.m.