Triple
T1219988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen's University at Kingston |
E26197
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Queen's
Queen's is a prestigious public research university located in Kingston, Ontario, Canada, known for its strong academic programs and historic campus.
|
E139955
|
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: Queen's | Statement: [Queen's University at Kingston, shortName, Queen's]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen's Context triple: [Queen's University at Kingston, shortName, Queen's]
-
A.
Queen
A queen is a female monarch who serves as the sovereign head of state in a monarchy.
-
B.
Queen B
Queen B is the nickname of Lil' Kim, an influential American rapper known for her provocative style, hardcore lyrics, and pioneering role for women in hip-hop.
-
C.
King
King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
-
D.
King
The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
-
E.
King
King is a township in the Regional Municipality of York in Ontario, Canada, known for its rural landscapes, rolling hills, and equestrian farms within the Greater Toronto Area.
- 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: Queen's Triple: [Queen's University at Kingston, shortName, Queen's]
Generated description
Queen's is a prestigious public research university located in Kingston, Ontario, Canada, known for its strong academic programs and historic campus.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Queen's Target entity description: Queen's is a prestigious public research university located in Kingston, Ontario, Canada, known for its strong academic programs and historic campus.
-
A.
Queen
A queen is a female monarch who serves as the sovereign head of state in a monarchy.
-
B.
Queen B
Queen B is the nickname of Lil' Kim, an influential American rapper known for her provocative style, hardcore lyrics, and pioneering role for women in hip-hop.
-
C.
King
King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
-
D.
King
The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
-
E.
King
King is a township in the Regional Municipality of York in Ontario, Canada, known for its rural landscapes, rolling hills, and equestrian farms within the Greater Toronto Area.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1ead088190bf44dc6ab1edf18b |
completed | March 1, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8322425c81909cc206b122416c43 |
completed | March 7, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69ac83de917c8190adf5effc6ecebeb4 |
completed | March 7, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac84c392a08190854da8405c0252b2 |
completed | March 7, 2026, 8:04 p.m. |
Created at: March 1, 2026, 7:46 p.m.