Triple
T19255092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander von Branca |
E481495
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | von Branca |
—
|
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: von Branca | Statement: [Alexander von Branca, familyName, von Branca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: von Branca Context triple: [Alexander von Branca, familyName, von Branca]
-
A.
Alexander von Branca
chosen
Alexander von Branca was a German architect known for his modernist and often monumental public buildings, including major museum and cultural projects in Munich.
-
B.
von Schlebrügge
von Schlebrügge is the aristocratic German-Swedish family name of Nena von Schlebrügge, a former fashion model and mother of actress Uma Thurman.
-
C.
von Bleibruck
Von Bleibruck is a German-language noble surname historically associated with Central European aristocratic lineages.
-
D.
van Bruggen
Van Bruggen is a Dutch surname most notably associated with Coosje van Bruggen, a prominent sculptor and art historian known for her large-scale public art collaborations.
-
E.
Blásy
Blásy is a Hungarian surname most notably associated with Eduard Blásy, a 19th-century astronomer.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb3459d08190a7c28ed3f8c82a97 |
completed | April 20, 2026, 10:08 a.m. |
Created at: April 10, 2026, 1:28 p.m.