Triple
T6755512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Township of South Dundas |
E154447
|
entity |
| Predicate | hasCommunity |
P2605
|
FINISHED |
| Object |
Glen Becker
Glen Becker is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
|
E670022
|
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: Glen Becker | Statement: [Township of South Dundas, hasCommunity, Glen Becker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glen Becker Context triple: [Township of South Dundas, hasCommunity, Glen Becker]
-
A.
Joe Becker
Joe Becker is a computer scientist best known as a co-founder of the Unicode Consortium and an early architect of the Unicode character encoding standard.
-
B.
Ben Becker
Ben Becker is a German actor known for his intense screen presence and roles in both film and theater.
-
C.
Joe Glauberg
Joe Glauberg is a television writer and producer best known for his work on the hit sitcom *Mork & Mindy*.
-
D.
Duane Schuler
Duane Schuler is an American theatrical lighting designer known for his work in opera, including major productions at leading opera houses.
-
E.
Arnie Becker
Arnie Becker is a charismatic, womanizing divorce attorney known for his flashy lifestyle and moral ambiguity on the television series "L.A. Law."
- 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: Glen Becker Triple: [Township of South Dundas, hasCommunity, Glen Becker]
Generated description
Glen Becker is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glen Becker Target entity description: Glen Becker is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
-
A.
Joe Becker
Joe Becker is a computer scientist best known as a co-founder of the Unicode Consortium and an early architect of the Unicode character encoding standard.
-
B.
Ben Becker
Ben Becker is a German actor known for his intense screen presence and roles in both film and theater.
-
C.
Joe Glauberg
Joe Glauberg is a television writer and producer best known for his work on the hit sitcom *Mork & Mindy*.
-
D.
Duane Schuler
Duane Schuler is an American theatrical lighting designer known for his work in opera, including major productions at leading opera houses.
-
E.
Arnie Becker
Arnie Becker is a charismatic, womanizing divorce attorney known for his flashy lifestyle and moral ambiguity on the television series "L.A. Law."
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1f5ab0881908619b835b9f068d4 |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845cc4f748190a666ab40b183cb3a |
completed | March 28, 2026, 9:19 p.m. |
| NEDg | Description generation | batch_69c8469df1c081908aef635dfa3d74f7 |
completed | March 28, 2026, 9:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8472c55c081909e189cf92c4c1a86 |
completed | March 28, 2026, 9:25 p.m. |
Created at: March 27, 2026, 2:11 p.m.