Triple
T3982772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behrens |
E86796
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Ralph Behrens
Ralph Behrens is a notable individual who prominently bears the surname Behrens.
|
E479981
|
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: Ralph Behrens | Statement: [Behrens, hasNotableBearer, Ralph Behrens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Behrens Context triple: [Behrens, hasNotableBearer, Ralph Behrens]
-
A.
George Boemler
George Boemler was a film editor known for his work on classic Hollywood productions, including the musical comedy "High Society."
-
B.
Carl Rinsch
Carl Rinsch is a film director and commercial filmmaker best known for directing the fantasy action movie "47 Ronin" starring Keanu Reeves.
-
C.
Harold Huber
Harold Huber was an American character actor known for his prolific work in 1930s and 1940s Hollywood films, often portraying suave or villainous supporting roles.
-
D.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
-
E.
Charles Rettig
Charles Rettig is an American tax attorney who served as the Commissioner of the Internal Revenue Service (IRS) from 2018 to 2022.
- 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: Ralph Behrens Triple: [Behrens, hasNotableBearer, Ralph Behrens]
Generated description
Ralph Behrens is a notable individual who prominently bears the surname Behrens.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ralph Behrens Target entity description: Ralph Behrens is a notable individual who prominently bears the surname Behrens.
-
A.
George Boemler
George Boemler was a film editor known for his work on classic Hollywood productions, including the musical comedy "High Society."
-
B.
Carl Rinsch
Carl Rinsch is a film director and commercial filmmaker best known for directing the fantasy action movie "47 Ronin" starring Keanu Reeves.
-
C.
Harold Huber
Harold Huber was an American character actor known for his prolific work in 1930s and 1940s Hollywood films, often portraying suave or villainous supporting roles.
-
D.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
-
E.
Charles Rettig
Charles Rettig is an American tax attorney who served as the Commissioner of the Internal Revenue Service (IRS) from 2018 to 2022.
- F. None of above. chosen
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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9dd351c81909605bc2605f541e1 |
completed | March 9, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be777b514081909832a8a520a7f7d1 |
completed | March 21, 2026, 10:48 a.m. |
| NEDg | Description generation | batch_69be77fbb3008190bf1b4066a2dbff81 |
completed | March 21, 2026, 10:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be7854677c8190aeef107e6874e4cf |
completed | March 21, 2026, 10:52 a.m. |
Created at: March 9, 2026, 3:33 p.m.