Triple
T15219824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ndau people |
E363735
|
entity |
| Predicate | linguisticCode |
P36930
|
FINISHED |
| Object | ISO 639-3: ndc |
—
|
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: ISO 639-3: ndc | Statement: [Ndau people, linguisticCode, ISO 639-3: ndc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticCode Context triple: [Ndau people, linguisticCode, ISO 639-3: ndc]
-
A.
hasLinguisticCode
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
-
B.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
C.
languageCodeISO639-1
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
-
D.
ISO639-3CodeOfLanguage
chosen
Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
-
E.
languageCodeStandard
Indicates that a language code conforms to a specific standardized coding scheme (such as ISO language code standards).
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007709d3881908384f0fe1e0218d0 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.