Triple
T17785715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daddy, Daddy |
E444011
|
entity |
| Predicate | hasWorkLanguageContext |
P8383
|
FINISHED |
| Object | global contemporary art |
—
|
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: global contemporary art | Statement: [Daddy, Daddy, hasWorkLanguageContext, global contemporary art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkLanguageContext Context triple: [Daddy, Daddy, hasWorkLanguageContext, global contemporary art]
-
A.
hasLanguageContext
chosen
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
hasWorkContext
Indicates that an entity is associated with a particular work-related situation, environment, or context in which it is relevant or applies.
-
C.
hasWorkedInLanguage
Indicates that an entity has performed work or professional activities using a particular language.
-
D.
hasOfficialLanguageOfWork
Indicates that an entity uses a specified language as its official medium for conducting work or formal activities.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48792b1c48190836141cfc6656cdd |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.