Triple
T12576395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monguor (Tu) language |
E300215
|
entity |
| Predicate | contactWithLanguage |
P95982
|
FINISHED |
| Object | Chinese |
—
|
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: Chinese | Statement: [Monguor (Tu) language, contactWithLanguage, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contactWithLanguage Context triple: [Monguor (Tu) language, contactWithLanguage, Chinese]
-
A.
contactLanguageWith
Indicates that two entities communicate with each other using a particular language as the medium of contact.
-
B.
contactWith
Indicates that two entities are in direct or indirect physical or communicative interaction or touch with each other.
-
C.
hasContactWithLanguage
chosen
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
-
D.
primaryLanguageContact
Indicates that one language serves as the main or dominant medium of communication in a particular contact situation between language communities.
-
E.
usedAsContactLanguageBetween
Indicates that a language functions as the medium of communication between two or more distinct language communities.
- 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.