Triple
T15873759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | རྫོང་ཁ |
E384893
|
entity |
| Predicate | belongsToMacrolanguageGroup |
P23525
|
FINISHED |
| Object | Tibetic macrolanguage |
—
|
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: Tibetic macrolanguage | Statement: [རྫོང་ཁ, belongsToMacrolanguageGroup, Tibetic macrolanguage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToMacrolanguageGroup Context triple: [རྫོང་ཁ, belongsToMacrolanguageGroup, Tibetic macrolanguage]
-
A.
macrolanguageGrouping
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
-
B.
macrolanguageMemberOf
chosen
Indicates that a language variety is classified as a member of a larger macrolanguage grouping.
-
C.
hasLanguageGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
-
D.
hasISO639MacrolanguageCode
Indicates that a language entity is associated with a specific ISO 639 macrolanguage code that represents a broader language grouping.
-
E.
isMacrolanguageCode
Indicates that a language code represents a macrolanguage encompassing multiple individual language varieties or codes.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.