Triple
T23983231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Youth Front |
E604560
|
entity |
| Predicate | languageAssociatedWithName |
P15
|
FINISHED |
| Object | Malay |
—
|
NE NERFINISHED |
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 | Statement: [Youth Front, languageAssociatedWithName, Malay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAssociatedWithName Context triple: [Youth Front, languageAssociatedWithName, Malay]
-
A.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
B.
languageAssociation
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
E.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
- 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2bf02fc8190bebd59f149e0bbfc |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:30 p.m.