Triple
T94506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Rogers |
E1898
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Lisa Rogers
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
|
E54917
|
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: Lisa Rogers | Statement: [Ted Rogers, hasChild, Lisa Rogers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisa Rogers Context triple: [Ted Rogers, hasChild, Lisa Rogers]
-
A.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
B.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
C.
Ann Sadler
Ann Sadler was the wife of John Harvard, the English clergyman and benefactor after whom Harvard University is named.
-
D.
Lynnette Armstrong
Lynnette Armstrong is a notable individual recognized for achievements significant enough to be associated with the surname Armstrong.
-
E.
Colleen Bell
Colleen Bell is an American television producer and political appointee who served as the U.S. Ambassador to Hungary.
- 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: Lisa Rogers Triple: [Ted Rogers, hasChild, Lisa Rogers]
Generated description
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lisa Rogers Target entity description: Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
-
A.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
B.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
C.
Ann Sadler
Ann Sadler was the wife of John Harvard, the English clergyman and benefactor after whom Harvard University is named.
-
D.
Lynnette Armstrong
Lynnette Armstrong is a notable individual recognized for achievements significant enough to be associated with the surname Armstrong.
-
E.
Colleen Bell
Colleen Bell is an American television producer and political appointee who served as the U.S. Ambassador to Hungary.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24fd4777c81909ea9b9a6bd4f7ad5 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a431d8941c8190b6336ccdbb33cc5b |
completed | March 1, 2026, 12:32 p.m. |
| NEDg | Description generation | batch_69a4320b5b08819098ca871f5fbc1a3b |
completed | March 1, 2026, 12:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a43503ddc48190b2a84ddd5cc39290 |
completed | March 1, 2026, 12:45 p.m. |
Created at: Feb. 28, 2026, 2:09 a.m.