Triple
T1509148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aaron Burr |
E33973
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Burr
Burr is a surname most famously associated with Aaron Burr, the third vice president of the United States who dueled Alexander Hamilton.
|
E173165
|
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: Burr | Statement: [Aaron Burr, familyName, Burr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burr Context triple: [Aaron Burr, familyName, Burr]
-
A.
Hobuck
Hobuck is the original settlement name that preceded the modern city of Hoboken, New Jersey.
-
B.
Pesky's Pole
Pesky's Pole is the famously short right-field foul pole at Boston's Fenway Park, named after Red Sox player Johnny Pesky and known for its role in several memorable home runs.
-
C.
Butler
Butler is a city in Pennsylvania that serves as the administrative and economic center of Butler County.
-
D.
Butler
Butler is the party that served as the defendant in the landmark U.S. Supreme Court case United States v. Butler, which addressed the constitutionality of certain New Deal agricultural policies.
-
E.
Burton
Burton is the surname of acclaimed American filmmaker Tim Burton, known for his dark, gothic, and whimsical visual style.
- 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: Burr Triple: [Aaron Burr, familyName, Burr]
Generated description
Burr is a surname most famously associated with Aaron Burr, the third vice president of the United States who dueled Alexander Hamilton.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Burr Target entity description: Burr is a surname most famously associated with Aaron Burr, the third vice president of the United States who dueled Alexander Hamilton.
-
A.
Hobuck
Hobuck is the original settlement name that preceded the modern city of Hoboken, New Jersey.
-
B.
Pesky's Pole
Pesky's Pole is the famously short right-field foul pole at Boston's Fenway Park, named after Red Sox player Johnny Pesky and known for its role in several memorable home runs.
-
C.
Butler
Butler is a city in Pennsylvania that serves as the administrative and economic center of Butler County.
-
D.
Butler
Butler is the party that served as the defendant in the landmark U.S. Supreme Court case United States v. Butler, which addressed the constitutionality of certain New Deal agricultural policies.
-
E.
Burton
Burton is the surname of acclaimed American filmmaker Tim Burton, known for his dark, gothic, and whimsical visual style.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8891daf708190a23d6c920eac8b6d |
completed | March 4, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad233c254c8190b52b34526c9cb3cb |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad242d20448190a27ff7414d9cff21 |
completed | March 8, 2026, 7:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad24e6e9688190a20c67c181936e98 |
completed | March 8, 2026, 7:27 a.m. |
Created at: March 4, 2026, 7:24 p.m.