Triple
T25332988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralte |
E635201
|
entity |
| Predicate | hasLanguageAffinity |
P145372
|
FINISHED |
| Object | Mizo language |
—
|
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: Mizo language | Statement: [Ralte, hasLanguageAffinity, Mizo language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageAffinity Context triple: [Ralte, hasLanguageAffinity, Mizo language]
-
A.
hasLanguageSimilarTo
Indicates that one entity uses or is associated with a language that is similar or closely related to the language used or associated with another entity.
-
B.
hasLinguisticAffiliation
chosen
Indicates a relationship where an entity is associated with or belongs to a particular language or linguistic group.
-
C.
hasContactWithLanguage
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
-
D.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
E.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
- 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_69e75a9908108190a95427a97020632a |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 21, 2026, 1:30 p.m.