Triple
T21608994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinetic art |
E533248
|
entity |
| Predicate | hasNotableArtist |
P2487
|
FINISHED |
| Object | Yaacov Agam |
—
|
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: Yaacov Agam | Statement: [Kinetic art, hasNotableArtist, Yaacov Agam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yaacov Agam Context triple: [Kinetic art, hasNotableArtist, Yaacov Agam]
-
A.
Yaacov Agam
chosen
Yaacov Agam is an Israeli sculptor and experimental artist renowned as a pioneer of kinetic and optical art.
-
B.
Yona Friedman
Yona Friedman was a visionary Hungarian-French architect and urban planner known for his influential theories on mobile architecture and participatory, flexible urban design.
-
C.
Leon Reiser
Leon Reiser is the son of American actor and comedian Paul Reiser.
-
D.
Leo Kahn
Leo Kahn was an American entrepreneur and retail pioneer best known as a co-founder of the office-supplies giant Staples.
-
E.
Leon Breiner
Leon Breiner was a white neighbor who was shot and killed during the 1925 Ossian Sweet incident in Detroit, a racially charged confrontation that led to a landmark civil rights trial.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e7005c81908cfa86358b8dbef1 |
completed | April 27, 2026, 8:01 a.m. |
Created at: April 16, 2026, 6:33 p.m.