Triple
T1972507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Burnet Tuthill |
E42831
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object |
Burnet
Burnet is the middle name of William Burnet Tuthill, the American architect best known for designing New York’s Carnegie Hall.
|
E223865
|
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: Burnet | Statement: [William Burnet Tuthill, middleName, Burnet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burnet Context triple: [William Burnet Tuthill, middleName, Burnet]
-
A.
Burnett
Burnett is a surname most famously associated with American comedian and actress Carol Burnett, a pioneering figure in television sketch comedy.
-
B.
Brewster
Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
-
C.
Brewster
Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
-
D.
Brewster
Brewster is an English occupational surname historically associated with brewing ale or beer.
-
E.
Brewster
Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
- 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: Burnet Triple: [William Burnet Tuthill, middleName, Burnet]
Generated description
Burnet is the middle name of William Burnet Tuthill, the American architect best known for designing New York’s Carnegie Hall.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Burnet Target entity description: Burnet is the middle name of William Burnet Tuthill, the American architect best known for designing New York’s Carnegie Hall.
-
A.
Burnett
Burnett is a surname most famously associated with American comedian and actress Carol Burnett, a pioneering figure in television sketch comedy.
-
B.
Brewster
Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
-
C.
Brewster
Brewster is an English occupational surname historically associated with brewing ale or beer.
-
D.
Brewster
Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
-
E.
Brewster
Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f275408190affa93f8cb6a8184 |
completed | March 7, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032368508190a67fae314d0e6b21 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae057cc1a08190895031fa6c095f49 |
completed | March 8, 2026, 11:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0751eff4819086e5469a2c56a24d |
completed | March 8, 2026, 11:33 p.m. |
Created at: March 4, 2026, 7:36 p.m.