Triple
T19371557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan Bulkeley |
E484550
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Bulkeley
Bulkeley is an English-origin surname historically associated with several notable political and social figures, particularly in the United States and the United Kingdom.
|
E1372809
|
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: Bulkeley | Statement: [Morgan Bulkeley, familyName, Bulkeley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bulkeley Context triple: [Morgan Bulkeley, familyName, Bulkeley]
-
A.
Belknap
Belknap is a surname most notably associated with American actress Anna Belknap, known for her role on the television series "CSI: NY."
-
B.
Albany Hancock
Albany Hancock was a 19th-century English naturalist and malacologist known for his influential studies of marine invertebrates, particularly nudibranchs.
-
C.
Lamont
Lamont is a surname of Scottish origin borne by various notable individuals in politics, finance, academia, and the arts.
-
D.
Lamont
Lamont is an unincorporated community in Kern County, California, known primarily as an agricultural and residential area near Bakersfield.
-
E.
Bancroft
Bancroft is an English-origin surname borne by various notable figures in politics, academia, and the arts.
- 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: Bulkeley Triple: [Morgan Bulkeley, familyName, Bulkeley]
Generated description
Bulkeley is an English-origin surname historically associated with several notable political and social figures, particularly in the United States and the United Kingdom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bulkeley Target entity description: Bulkeley is an English-origin surname historically associated with several notable political and social figures, particularly in the United States and the United Kingdom.
-
A.
Belknap
Belknap is a surname most notably associated with American actress Anna Belknap, known for her role on the television series "CSI: NY."
-
B.
Albany Hancock
Albany Hancock was a 19th-century English naturalist and malacologist known for his influential studies of marine invertebrates, particularly nudibranchs.
-
C.
Lamont
Lamont is a surname of Scottish origin borne by various notable individuals in politics, finance, academia, and the arts.
-
D.
Lamont
Lamont is an unincorporated community in Kern County, California, known primarily as an agricultural and residential area near Bakersfield.
-
E.
Bancroft
Bancroft is an English-origin surname borne by various notable figures in politics, academia, and the arts.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e619b09ef08190a8b420316c0b8eb3 |
completed | April 20, 2026, 12:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07241bc0208190863311598a29eede |
completed | May 15, 2026, 1:48 p.m. |
| NEDg | Description generation | batch_6a07276885a88190b1711a1735de7c26 |
completed | May 15, 2026, 2:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07282bf05c819096292fc6a6f5db82 |
completed | May 15, 2026, 2:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.