Triple
T2665819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernhard Caesar Einstein |
E55632
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bernhard |
E38564
|
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: Bernhard | Statement: [Bernhard Caesar Einstein, givenName, Bernhard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernhard Context triple: [Bernhard Caesar Einstein, givenName, Bernhard]
-
A.
Bernhard
chosen
Bernhard is a male given name of Germanic origin, historically borne by various European nobles and royals, including Prince Bernhard of the Netherlands.
-
B.
Bernharda
Bernharda is a feminine given name, primarily used in Central and Eastern Europe, derived from the masculine name Bernhard.
-
C.
Othmar
Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
-
D.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
E.
Ernst
Ernst is a masculine given name of Germanic origin, commonly used in German-speaking 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96ed2748190a4feae98199b459d |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6382a2081909ea7216c19a65e7e |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:54 p.m.