Triple
T16603027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Behrens |
E403379
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Behrens |
E403379
|
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: John Behrens | Statement: [John Behrens, name, John Behrens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Behrens Context triple: [John Behrens, name, John Behrens]
-
A.
John Behrens
chosen
John Behrens is a person notable enough to be specifically identified as a bearer of the surname Behrens.
-
B.
Heinz Behrens
Heinz Behrens was a German actor best known for his roles in East German film and television productions.
-
C.
Wulf Behrens
Wulf Behrens is a person notable enough to be recognized as a bearer of the surname Behrens, though specific public details about his life or achievements are not widely documented.
-
D.
Walter-Ulrich Behrens
Walter-Ulrich Behrens was a German statistician known for his contributions to the development of small-sample statistical methods, including work related to what is now called the Behrens–Fisher problem.
-
E.
Paul Behrens
Paul Behrens is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Behrens.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d77d97c8190a63330897e49a9c9 |
completed | April 18, 2026, 10:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084b233ac8190b3f1ab82a47110d4 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:17 a.m.