Triple
T1153626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josef Mengele |
E23732
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Josef
Josef is a masculine given name of Hebrew origin, commonly used in various European languages as a form of Joseph.
|
E117285
|
NE FINISHED |
How this triple was built (4 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: Josef | Statement: [Josef Mengele, givenName, Josef]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Josef Context triple: [Josef Mengele, givenName, Josef]
-
A.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
B.
Franz
Franz is the given name of Franz Cardinal König, a prominent 20th-century Austrian Catholic cardinal and influential church leader.
-
C.
Eduard
Eduard was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
-
D.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
E.
Josef Oberhauser
Josef Oberhauser was an SS officer who participated in the Nazi extermination program during the Holocaust, including involvement in the operations of the Belzec death camp.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Josef Triple: [Josef Mengele, givenName, Josef]
Generated description
Josef is a masculine given name of Hebrew origin, commonly used in various European languages as a form of Joseph.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Josef Target entity description: Josef is a masculine given name of Hebrew origin, commonly used in various European languages as a form of Joseph.
-
A.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
B.
Franz
Franz is the given name of Franz Cardinal König, a prominent 20th-century Austrian Catholic cardinal and influential church leader.
-
C.
Eduard
Eduard was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
-
D.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
E.
Josef Oberhauser
chosen
Josef Oberhauser was an SS officer who participated in the Nazi extermination program during the Holocaust, including involvement in the operations of the Belzec death camp.
- F. None of above.
Provenance (5 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8e9cb481908a528a828b21d497 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad7967a0fc8190822b70438f0b2c35 |
completed | March 8, 2026, 1:28 p.m. |
| NEDg | Description generation | batch_69ad7ad406f881908104cfee6374d83c |
completed | March 8, 2026, 1:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad7b2918ac81908d1a364320c0aef3 |
completed | March 8, 2026, 1:35 p.m. |
Created at: March 1, 2026, 7:44 p.m.