Triple
T810975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emil du Bois-Reymond |
E17543
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Emil |
E22883
|
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: Emil | Statement: [Emil du Bois-Reymond, givenName, Emil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emil Context triple: [Emil du Bois-Reymond, givenName, Emil]
-
A.
Emil
chosen
Emil is the given name of Carl Gustaf Emil Mannerheim, the renowned Finnish military leader and statesman who served as President of Finland.
-
B.
Oskar
Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
-
C.
Hans
Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
-
D.
Franz
Franz is the given name of Franz Cardinal König, a prominent 20th-century Austrian Catholic cardinal and influential church leader.
-
E.
Eduard
Eduard was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab282fe48190a05ee97550843cd7 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac427da0348190a8ae16db2a048d0b |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:38 p.m.