Triple
T2562498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing dialect |
E57272
|
entity |
| Predicate | hasLexicalBasisFor |
P2565
|
FINISHED |
| Object | core vocabulary of Standard 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: core vocabulary of Standard Chinese | Statement: [Beijing dialect, hasLexicalBasisFor, core vocabulary of Standard Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexicalBasisFor Context triple: [Beijing dialect, hasLexicalBasisFor, core vocabulary of Standard Chinese]
-
A.
hasLexicalInfluenceOn
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
B.
hasLexicalReconstruction
Indicates that there exists a hypothesized or reconstructed lexical form corresponding to a word or expression, typically inferred for an earlier or unattested stage of a language.
-
C.
isBackboneOf
chosen
Indicates that one entity forms the main supporting structure or central framework upon which another entity fundamentally depends.
-
D.
hasGivenNameBasis
Indicates that one entity’s given name is derived from, based on, or formed using another entity (such as a name, word, or person) as its basis.
-
E.
hasLexicalSimilarityWith
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.