Triple
T267980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Standard Time |
E5773
|
entity |
| Predicate | usedForFinancialMarkets |
P724
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [China Standard Time, usedForFinancialMarkets, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForFinancialMarkets Context triple: [China Standard Time, usedForFinancialMarkets, yes]
-
A.
usedByFinancialMarket
chosen
Indicates that something is employed or utilized within the operations, practices, or mechanisms of a financial market.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
marketType
Indicates the classification or category of market in which an entity operates or a transaction occurs (e.g., retail, wholesale, online).
-
D.
isMostTradedCurrency
Indicates that a currency is the one with the highest trading volume or frequency in a given market or context.
-
E.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.