Triple
T25284538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Depositary Share |
E633900
|
entity |
| Predicate | hasMarketRisk |
P150650
|
FINISHED |
| Object | foreign exchange risk via underlying currency |
—
|
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: foreign exchange risk via underlying currency | Statement: [American Depositary Share, hasMarketRisk, foreign exchange risk via underlying currency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketRisk Context triple: [American Depositary Share, hasMarketRisk, foreign exchange risk via underlying currency]
-
A.
isSubjectToMarketRisk
chosen
Indicates that an entity is exposed to potential financial loss or variability in value due to changes in market conditions such as prices, interest rates, or exchange rates.
-
B.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
C.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
D.
hasRiskStatus
Indicates the level or category of risk currently associated with an entity.
-
E.
hasMarketData
Indicates that an entity possesses or is associated with relevant market-related information or statistics.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 21, 2026, 1:19 p.m.