Triple
T10899958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claus Wellenreuther |
E257410
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Claus |
E396023
|
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: Claus | Statement: [Claus Wellenreuther, hasGivenName, Claus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claus Context triple: [Claus Wellenreuther, hasGivenName, Claus]
-
A.
Claus
chosen
Claus was the German-born Prince Consort of Queen Beatrix of the Netherlands, known formally as Prince Claus of the Netherlands.
-
B.
Fanny Claus
Fanny Claus was a 19th-century French woman known primarily as a close friend and frequent model of painter Édouard Manet, notably appearing in his work "The Balcony."
-
C.
Klaas
Klaas is a masculine given name of Dutch origin commonly used in the Netherlands and Belgium.
-
D.
Bruno
Bruno is a masculine given name of Germanic origin, commonly used in various European and Latin American countries.
-
E.
Klausi
Klausi is a German diminutive form of the male given name Klaus, often used as an affectionate nickname.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a2f02881908b70be6499dd8d98 |
completed | April 9, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e155306e9081909433522eeecf2b7d |
completed | April 16, 2026, 9:31 p.m. |
Created at: April 8, 2026, 9:21 p.m.