Triple
T1889680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broken Chair |
E41841
|
entity |
| Predicate | designer |
P184
|
FINISHED |
| Object | Daniel Berset |
E210180
|
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: Daniel Berset | Statement: [Broken Chair, designer, Daniel Berset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Berset Context triple: [Broken Chair, designer, Daniel Berset]
-
A.
Daniel Berset
chosen
Daniel Berset is a Swiss artist and sculptor best known for creating the monumental "Broken Chair" installation in Geneva, a symbol of opposition to landmines and armed violence.
-
B.
Micheline Calmy-Rey
Micheline Calmy-Rey is a Swiss politician and former member of the Swiss Federal Council who served as Switzerland’s foreign minister and twice as President of the Swiss Confederation.
-
C.
André Calmy
André Calmy is the husband of Swiss politician and former President Micheline Calmy-Rey.
-
D.
Corine Mauch
Corine Mauch is a Swiss politician who has served as the mayor of Zurich and is known as the city’s first openly lesbian leader.
-
E.
François Chollet
François Chollet is a French software engineer and AI researcher best known as the creator of the Keras deep learning library and a prominent advocate for practical, human-centric machine learning.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb142e41881908fc7335673a9dec3 |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeae81e4c8190bf480215a8a33630 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:34 p.m.