Triple
T458246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor of Toronto |
E7277
|
entity |
| Predicate | hasHadOfficeHolder |
P9949
|
FINISHED |
| Object |
June Rowlands
June Rowlands was a Canadian politician who became the first woman to serve as mayor of Toronto, leading the city in the early 1990s.
|
E170910
|
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: June Rowlands | Statement: [Mayor of Toronto, hasHadOfficeHolder, June Rowlands]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: June Rowlands Context triple: [Mayor of Toronto, hasHadOfficeHolder, June Rowlands]
-
A.
Joan Barclay
Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
-
B.
Gladys Brockwell
Gladys Brockwell was an American stage and silent film actress known for her intense dramatic roles during the early 20th century.
-
C.
Yvonne Roberts
Yvonne Roberts is a British journalist and writer known for her work on social issues, politics, and feminism.
-
D.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
E.
Nora Barlow
Nora Barlow was a British botanist and editor best known as Charles Darwin’s granddaughter and for publishing and annotating key editions of his works and correspondence.
- 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: June Rowlands Triple: [Mayor of Toronto, hasHadOfficeHolder, June Rowlands]
Generated description
June Rowlands was a Canadian politician who became the first woman to serve as mayor of Toronto, leading the city in the early 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: June Rowlands Target entity description: June Rowlands was a Canadian politician who became the first woman to serve as mayor of Toronto, leading the city in the early 1990s.
-
A.
Joan Barclay
Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
-
B.
Gladys Brockwell
Gladys Brockwell was an American stage and silent film actress known for her intense dramatic roles during the early 20th century.
-
C.
Yvonne Roberts
Yvonne Roberts is a British journalist and writer known for her work on social issues, politics, and feminism.
-
D.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
E.
Nora Barlow
Nora Barlow was a British botanist and editor best known as Charles Darwin’s granddaughter and for publishing and annotating key editions of his works and correspondence.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2f01ec5148190b74e1727712f1163 |
completed | Feb. 28, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c8436008190b47e6a740eb20397 |
completed | March 8, 2026, 6:51 a.m. |
| NEDg | Description generation | batch_69ad1f36eaac8190a07a1faf57aa2c44 |
completed | March 8, 2026, 7:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad1f8cb0f081909c09c7032b517581 |
completed | March 8, 2026, 7:04 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.