Triple
T15533775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toby Emmerich |
E370289
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Emmerich |
E879302
|
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: Emmerich | Statement: [Toby Emmerich, familyName, Emmerich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emmerich Context triple: [Toby Emmerich, familyName, Emmerich]
-
A.
Emmerich
chosen
Emmerich is the German form of the given name Imre, used primarily in German-speaking regions.
-
B.
Veit
Veit is a German surname most notably associated with the 19th-century Romantic painter Philipp Veit.
-
C.
Jürgens
Jürgens is a German surname most notably associated with the Austrian-German actor Curt Jürgens.
-
D.
Reimund
Reimund is a masculine given name, primarily used in German-speaking regions, that is a variant of the name Raymond.
-
E.
Erwin
Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414877d88190804ee76566004e13 |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5e82a48190bb0a10ebc2412129 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:06 a.m.