Triple
T5983558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Asian languages |
E133173
|
entity |
| Predicate | loanSource |
P67731
|
FINISHED |
| Object | Sino-Xenic vocabulary |
—
|
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: Sino-Xenic vocabulary | Statement: [East Asian languages, loanSource, Sino-Xenic vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loanSource Context triple: [East Asian languages, loanSource, Sino-Xenic vocabulary]
-
A.
loanType
Indicates the specific category or kind of loan associated with an entity or transaction.
-
B.
lender
Indicates a relationship where one party provides something, typically money or resources, to another with the expectation of repayment or return.
-
C.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
D.
loanStructure
Indicates the specific terms, components, and repayment arrangement that define how a loan is organized between parties.
-
E.
lendingArm
Indicates that one entity provides financial support or resources to another, typically in the form of a loan or credit.
- F. None of above. chosen
Provenance (4 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a6c4f2481909cdcf931331b3595 |
completed | March 22, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04a663a4481908983048c69cba6b6 |
completed | March 22, 2026, 8 p.m. |
Created at: March 22, 2026, 4:04 p.m.