Triple
T24095119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beautiful Loser |
E596894
|
entity |
| Predicate | mainlyMarketedIn |
P130611
|
FINISHED |
| Object | North America |
—
|
NE NERFINISHED |
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: North America | Statement: [Beautiful Loser, mainlyMarketedIn, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyMarketedIn Context triple: [Beautiful Loser, mainlyMarketedIn, North America]
-
A.
countryOfFirstMarketing
Indicates the country where a product was first introduced or made available on the market.
-
B.
dominantMediaMarket
Indicates that one media market holds primary influence or control over another media market in terms of audience reach or content distribution.
-
C.
mainlyObservedIn
chosen
Indicates that something occurs, appears, or is found predominantly within a particular context, location, group, or condition.
-
D.
launchedInCountry
Indicates that an entity (such as a product, service, or mission) was officially initiated, introduced, or started within a specified country.
-
E.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
- 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_69e288c548048190a5c1018da1166a21 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dd24ad9c8190ae81bcc5eae6e159 |
completed | April 29, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:58 p.m.