Triple
T7123327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish Gold Coast |
E165997
|
entity |
| Predicate | languageUsedInTrade |
P74986
|
FINISHED |
| Object | Danish |
—
|
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: Danish | Statement: [Danish Gold Coast, languageUsedInTrade, Danish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedInTrade Context triple: [Danish Gold Coast, languageUsedInTrade, Danish]
-
A.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
B.
languageOfNegotiation
Indicates that a specified language is used as the medium of communication during a negotiation between parties.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageOfPrimaryMarkets
Indicates the primary language or languages used in the main markets where an entity operates or targets its products or services.
-
E.
valuedLanguage
Indicates that one entity considers a particular language important, appreciated, or held in high regard.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64ab1f881908bc2468cc72d2544 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:44 p.m.