Triple
T9949284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butz |
E195286
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Peter Butz
Peter Butz is an individual notable enough to be recognized as a prominent bearer of the surname Butz.
|
E837898
|
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: Peter Butz | Statement: [Butz, hasNotableBearer, Peter Butz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Butz Context triple: [Butz, hasNotableBearer, Peter Butz]
-
A.
Arthur Butz
Arthur Butz is an American electrical engineering professor best known for his controversial Holocaust denial writings.
-
B.
Albert Butz
Albert Butz was a Swiss-born American inventor and businessman best known for creating an early thermostat and founding the company that would later become part of Honeywell.
-
C.
Thomas Butz
Thomas Butz is a person notable enough to be specifically cited as a bearer of the surname Butz.
-
D.
Norbert Leo Butz
Norbert Leo Butz is a Tony Award–winning American stage actor and singer best known for his leading roles in major Broadway musicals such as Dirty Rotten Scoundrels and Catch Me If You Can.
-
E.
Martin Butzer
Martin Butzer is the birth name of Martin Bucer, a prominent 16th-century Protestant Reformer known for his efforts to mediate between differing branches of the Reformation.
- 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: Peter Butz Triple: [Butz, hasNotableBearer, Peter Butz]
Generated description
Peter Butz is an individual notable enough to be recognized as a prominent bearer of the surname Butz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Butz Target entity description: Peter Butz is an individual notable enough to be recognized as a prominent bearer of the surname Butz.
-
A.
Arthur Butz
Arthur Butz is an American electrical engineering professor best known for his controversial Holocaust denial writings.
-
B.
Albert Butz
Albert Butz was a Swiss-born American inventor and businessman best known for creating an early thermostat and founding the company that would later become part of Honeywell.
-
C.
Thomas Butz
Thomas Butz is a person notable enough to be specifically cited as a bearer of the surname Butz.
-
D.
Norbert Leo Butz
Norbert Leo Butz is a Tony Award–winning American stage actor and singer best known for his leading roles in major Broadway musicals such as Dirty Rotten Scoundrels and Catch Me If You Can.
-
E.
Martin Butzer
Martin Butzer is the birth name of Martin Bucer, a prominent 16th-century Protestant Reformer known for his efforts to mediate between differing branches of the Reformation.
- 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_69ca82e96a108190932bd1fc4acd73a0 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb65a4e6c8190968192a24aad1b7d |
completed | April 2, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d281d5f6188190a7e657b1bd9bc607 |
completed | April 5, 2026, 3:37 p.m. |
| NEDg | Description generation | batch_69d2860be32081909eec066c19552ba5 |
completed | April 5, 2026, 3:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2865c11c881909b6791bd2bf503c4 |
completed | April 5, 2026, 3:57 p.m. |
Created at: March 30, 2026, 8:45 p.m.