Triple
T910940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rufus Oldenburger Medal |
E19655
|
entity |
| Predicate | hasNotableRecipient |
P108
|
FINISHED |
| Object | Tamer Başar |
E62374
|
NE 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: Tamer Başar | Statement: [Rufus Oldenburger Medal, hasNotableRecipient, Tamer Başar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tamer Başar Context triple: [Rufus Oldenburger Medal, hasNotableRecipient, Tamer Başar]
-
A.
Tamer Başar
chosen
Tamer Başar is a prominent control theorist and engineer known for his influential contributions to dynamic games, stochastic control, and robust control theory.
-
B.
Oktay Caglar
Oktay Caglar is an entrepreneur best known as one of the co-founders of the online learning platform Udemy.
-
C.
Edip Cansever
Edip Cansever was a prominent 20th-century Turkish poet known for his modernist, introspective, and often experimental verse that helped shape contemporary Turkish poetry.
-
D.
Feridun Zaimoglu
Feridun Zaimoglu is a German-Turkish author and artist known for his influential novels, essays, and plays that explore migration, identity, and multicultural life in Germany.
-
E.
Koray Kavukcuoglu
Koray Kavukcuoglu is a prominent computer scientist and machine learning researcher known for his leadership in deep learning and artificial intelligence at DeepMind.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2de5b008190851852331db41324 |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c73d5bdc8190828cdf9f54e33a46 |
completed | March 4, 2026, 5:46 a.m. |
Created at: March 1, 2026, 7:39 p.m.