Triple
T21473491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Choiseul languages |
E529791
|
entity |
| Predicate | haveISO639Code |
P144496
|
FINISHED |
| Object | none (group level) |
—
|
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: none (group level) | Statement: [Choiseul languages, haveISO639Code, none (group level)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveISO639Code Context triple: [Choiseul languages, haveISO639Code, none (group level)]
-
A.
hasISO6393Code
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
-
B.
hasISO639MacrolanguageCode
Indicates that a language entity is associated with a specific ISO 639 macrolanguage code that represents a broader language grouping.
-
C.
hasISO639_5Code
Indicates that a language or language group is associated with a specific ISO 639-5 code that identifies it within the ISO 639-5 language classification standard.
-
D.
hasISO639LanguageCodeForMajorLanguage
Indicates that an entity is associated with a primary or major language identified by a specific ISO 639 language code.
-
E.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
- F. None of above. chosen
Provenance (4 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea156dac819087c4594d022d3df6 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:19 p.m.