Triple
T9288810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prospectus Regulation Rules |
E223463
|
entity |
| Predicate | appliesToMarketType |
P2821
|
FINISHED |
| Object | regulated markets |
—
|
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: regulated markets | Statement: [Prospectus Regulation Rules, appliesToMarketType, regulated markets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToMarketType Context triple: [Prospectus Regulation Rules, appliesToMarketType, regulated markets]
-
A.
supportsMarket
Indicates that one entity provides resources, infrastructure, or conditions that enable or facilitate the functioning or growth of a market associated with another entity.
-
B.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
C.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
D.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
E.
marketType
chosen
Indicates the classification or category of market in which an entity operates or a transaction occurs (e.g., retail, wholesale, online).
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0862b34c819097cb7c1777313925 |
completed | April 1, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69cc7a5aeb748190afb89c6bbd2a6d6f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:35 p.m.