Triple
T8732232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cesca Chair |
E207284
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Francesca Breuer |
E754975
|
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: Francesca Breuer | Statement: [Cesca Chair, namedAfter, Francesca Breuer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Francesca Breuer Context triple: [Cesca Chair, namedAfter, Francesca Breuer]
-
A.
Francesca Breuer
chosen
Francesca Breuer is the designer after whom the iconic modernist Cesca Chair is named.
-
B.
Annie Breuer
Annie Breuer is a notable individual associated with the surname Breuer, recognized as one of its distinguished bearers.
-
C.
Carla Breuer
Carla Breuer is a Dutch politician who serves as the mayor of the municipality of Teylingen in the Netherlands.
-
D.
Sophie Kauer
Sophie Kauer is a British-German cellist and actress best known for her breakout film debut in the 2022 psychological drama "Tár."
-
E.
Alexandra Papenfus
Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d2903b08190a5ef29b6d6ca5f1c |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf5174db7881908597d5dc472adde9 |
completed | April 3, 2026, 5:34 a.m. |
Created at: March 30, 2026, 6:37 p.m.