Triple
T10101893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schultz |
E216222
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Schulz |
E757721
|
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: Schulz | Statement: [Schultz, hasVariant, Schulz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schulz Context triple: [Schultz, hasVariant, Schulz]
-
A.
Schulz
chosen
Schulz is the birth surname of Lucia Moholy, the Czech-born photographer and writer associated with the Bauhaus movement.
-
B.
Schultz
Schultz is a surname of German origin borne by numerous notable individuals across fields such as entertainment, politics, and academia.
-
C.
Franz Schulz
Franz Schulz was a German-born screenwriter and playwright known for his work on European and Hollywood films in the early 20th century.
-
D.
Herr Schultz
Herr Schultz is a kindly, aging Jewish fruit-shop owner whose doomed romance with Fraulein Schneider provides a poignant emotional core to the musical *Cabaret*.
-
E.
Hans
Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd099c21c819097aac4f0f168a2da |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6d3efec8190b1432ca614aeb334 |
completed | April 5, 2026, 7:24 p.m. |
Created at: March 30, 2026, 9:02 p.m.