Triple
T14495386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius Wilford Arnstein |
E359482
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Arnstein |
E758104
|
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: Arnstein | Statement: [Julius Wilford Arnstein, familyName, Arnstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnstein Context triple: [Julius Wilford Arnstein, familyName, Arnstein]
-
A.
Arnstein
chosen
Arnstein is a town in the Mansfeld-Südharz district of Saxony-Anhalt, Germany, formed through the merger of several smaller municipalities.
-
B.
Eisenberg
Eisenberg is a small town in the German state of Thuringia that serves as an administrative and cultural center for its surrounding rural district.
-
C.
Eisenberg
Eisenberg is a surname most notably associated with American actress Hallie Kate Eisenberg.
-
D.
Brackman
Brackman is a character in John Grisham’s legal thriller novel "The Street Lawyer," involved in the story’s exploration of law, morality, and homelessness.
-
E.
Löwenthal
Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de93109cb081909a6e846db23a4635 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9544cc81908105554f212a9b8c |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:21 a.m.