Triple
T2297267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johann Georg Hamann |
E51646
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Johann |
E27352
|
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: Johann | Statement: [Johann Georg Hamann, givenName, Johann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johann Context triple: [Johann Georg Hamann, givenName, Johann]
-
A.
Johann
chosen
Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
-
B.
Johannes
Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
-
C.
Moritz
Moritz is a masculine given name of German origin, commonly used in German-speaking countries.
-
D.
Johan
Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
-
E.
Gottfried
Gottfried is the given name of Johann Gottfried Herder, an influential 18th-century German philosopher, theologian, and literary critic associated with the Sturm und Drang movement and early Romanticism.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5ddf00081909acb47cbd9a5f20e |
completed | March 7, 2026, 6:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af176e94c48190b1f913caa24bee02 |
completed | March 9, 2026, 6:54 p.m. |
Created at: March 4, 2026, 7:49 p.m.