Triple
T6164854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fry |
E137530
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
William Fry
William Fry is a prominent Irish corporate law firm known for its work in banking, finance, and commercial transactions.
|
E582332
|
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: William Fry | Statement: [Fry, hasNotableBearer, William Fry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Fry Context triple: [Fry, hasNotableBearer, William Fry]
-
A.
William J. Fry
William J. Fry was an architect known for his work on prominent U.S. government buildings in Washington, D.C., including contributions to the Old State, War, and Navy Building.
-
B.
George W. Frye
George W. Frye is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Frye.
-
C.
James Fawcett
James Fawcett was an architect best known for co-designing Melbourne’s iconic Flinders Street Station.
-
D.
Francis Smith
Francis Smith was a British Army officer best known for leading the regular troops during the opening engagements of the American Revolutionary War at Lexington and Concord in 1775.
-
E.
James Warren Sever
James Warren Sever was a Harvard University alumnus and benefactor after whom the historic Sever Hall in Harvard Yard is named.
- 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: William Fry Triple: [Fry, hasNotableBearer, William Fry]
Generated description
William Fry is a prominent Irish corporate law firm known for its work in banking, finance, and commercial transactions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: William Fry Target entity description: William Fry is a prominent Irish corporate law firm known for its work in banking, finance, and commercial transactions.
-
A.
William J. Fry
William J. Fry was an architect known for his work on prominent U.S. government buildings in Washington, D.C., including contributions to the Old State, War, and Navy Building.
-
B.
George W. Frye
George W. Frye is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Frye.
-
C.
James Fawcett
James Fawcett was an architect best known for co-designing Melbourne’s iconic Flinders Street Station.
-
D.
Francis Smith
Francis Smith was a British Army officer best known for leading the regular troops during the opening engagements of the American Revolutionary War at Lexington and Concord in 1775.
-
E.
James Warren Sever
James Warren Sever was a Harvard University alumnus and benefactor after whom the historic Sever Hall in Harvard Yard is named.
- 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_69c008a54fc88190b6ce4416490ca79d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d6225bc819097707be620681e7b |
completed | March 22, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c518ee96c48190afe3f42477f38856 |
completed | March 26, 2026, 11:30 a.m. |
| NEDg | Description generation | batch_69c52d49889c819096580c737231a765 |
completed | March 26, 2026, 12:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c58eb539a481909c5a279c1047cfd3 |
completed | March 26, 2026, 7:53 p.m. |
Created at: March 22, 2026, 4:17 p.m.