Triple
T33983486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nik & Jay |
E871348
|
entity |
| Predicate | hasNotableWorkLanguage |
P197658
|
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: [Nik & Jay, hasNotableWorkLanguage, Danish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableWorkLanguage Context triple: [Nik & Jay, hasNotableWorkLanguage, Danish]
-
A.
hasWorkedInLanguage
Indicates that an entity has performed work or professional activities using a particular language.
-
B.
containsWorkLanguage
chosen
Indicates that one entity includes or is associated with a specific language used for a work (such as a document, publication, or creative piece).
-
C.
hasAwardedWorkLanguage
Indicates the language in which an awarded work (such as a prize-winning book, film, or other creation) is expressed.
-
D.
hasOfficialLanguageOfWork
Indicates that an entity uses a specified language as its official medium for conducting work or formal activities.
-
E.
notableLanguageOfActivity
Indicates that a language is prominently used or recognized in connection with a particular activity or domain of activity.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a023f290e3081909a465d6cfb79518a |
completed | May 11, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_6a0238d1436c8190ab0251030b01902e |
completed | May 11, 2026, 8:15 p.m. |
Created at: May 1, 2026, 1:50 a.m.