Triple
T18181949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Kʼicheʼ |
E435307
|
entity |
| Predicate | hasISO639_3CodeOfParentLanguage |
P8719
|
FINISHED |
| Object | quc |
—
|
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: quc | Statement: [Southern Kʼicheʼ, hasISO639_3CodeOfParentLanguage, quc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISO639_3CodeOfParentLanguage Context triple: [Southern Kʼicheʼ, hasISO639_3CodeOfParentLanguage, quc]
-
A.
sharesISO639-3CodeWith
Indicates that two language entities share the same ISO 639-3 code, meaning they are treated as the same language in that coding system.
-
B.
hasISO6393Code
chosen
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
-
C.
ISO639-3CodeOfLanguage
Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
-
D.
hasPrimaryVernacularLanguageFamily
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
E.
hasSuperordinateLanguage
Indicates that one language serves as a higher-level, overarching, or more general language in relation to another language.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffb3bc88190a627be9c444d5c7d |
completed | April 19, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.