Triple
T20158178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isa Genzken |
E491631
|
entity |
| Predicate | creatorOf |
P806
|
FINISHED |
| Object | Rose II |
—
|
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: Rose II | Statement: [Isa Genzken, creatorOf, Rose II]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rose II Context triple: [Isa Genzken, creatorOf, Rose II]
-
A.
Rose II
chosen
Rose II is a large-scale public sculpture by German artist Isa Genzken, depicting an oversized single rose installed on the exterior of the New Museum in New York City.
-
B.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
C.
Isabella
Isabella was a Polish princess of the Jagiellonian dynasty who became Queen consort of Hungary in the 16th century.
-
D.
Isabella
Isabella was a 15th-century Aragonese princess who became Queen of Portugal through her marriage to King Manuel I.
-
E.
Isabella
Isabella was a Portuguese noblewoman of the House of Braganza who held the title of Duchess of Guimarães in the 16th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.