Triple
T12576406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monguor (Tu) language |
E300215
|
entity |
| Predicate | languageCodeGlottolog |
P3086
|
FINISHED |
| Object | mong1330 |
—
|
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: mong1330 | Statement: [Monguor (Tu) language, languageCodeGlottolog, mong1330]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCodeGlottolog Context triple: [Monguor (Tu) language, languageCodeGlottolog, mong1330]
-
A.
glottocode
chosen
Indicates the standardized Glottolog code that uniquely identifies the language or dialect associated with an entity.
-
B.
ISO639-3CodeOfLanguage
Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
-
C.
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.
-
D.
glottoCategory
Indicates the linguistic classification or type (such as language family, subgroup, or category) to which a language or dialect is assigned.
-
E.
ISO639-6Code
Indicates the standardized ISO 639-6 four-letter code that uniquely identifies a specific language variety or dialect.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 4:47 p.m.