Triple
T20071815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsar |
E499755
|
entity |
| Predicate | relatedTitle |
P914
|
FINISHED |
| Object | Kaiser |
—
|
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: Kaiser | Statement: [Tsar, relatedTitle, Kaiser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaiser Context triple: [Tsar, relatedTitle, Kaiser]
-
A.
Kaiser
chosen
Kaiser is the German imperial title historically used by the emperors of the German and Austro-Hungarian Empires, derived from the name and concept of the Roman "Caesar."
-
B.
Keizer
Keizer is a Dutch surname most notably associated with Piet Keizer, a celebrated footballer who starred for Ajax and the Netherlands in the 1960s and 1970s.
-
C.
Eisenhauer
Eisenhauer is a German-origin surname best known as the ancestral form of the name borne by U.S. President Dwight D. Eisenhower.
-
D.
Kais
Kais is the given name of Kais Saied, the Tunisian politician and president known for his anti-corruption stance and consolidation of executive power.
-
E.
Sieg
The Sieg is a river in western Germany that flows through North Rhine-Westphalia and Rhineland-Palatinate before joining the Rhine.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66438633481908710907c48806499 |
completed | April 20, 2026, 5:36 p.m. |
Created at: April 11, 2026, 3:40 p.m.