Triple
T1198798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nguni languages |
E25728
|
entity |
| Predicate | ISO639Grouping |
P3349
|
FINISHED |
| Object | nguni (informal subgroup) |
—
|
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: nguni (informal subgroup) | Statement: [Nguni languages, ISO639Grouping, nguni (informal subgroup)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISO639Grouping Context triple: [Nguni languages, ISO639Grouping, nguni (informal subgroup)]
-
A.
ISO639Macrolanguage
Indicates that a language variety is part of a broader ISO 639-defined macrolanguage grouping that encompasses multiple closely related individual languages.
-
B.
ISO639_3Status
Indicates the classification or status assigned to a language according to the ISO 639-3 standard (e.g., active, extinct, historical, constructed).
-
C.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
D.
hasLanguageGroup
chosen
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
-
E.
hasISO6393Code
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9c013c8190822d44d465d60fdb |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.