Triple
T3422448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boom Town |
E72143
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Karen Vanmeer
Karen Vanmeer is a fictional character from the Canadian television drama series "Boom Town."
|
E404358
|
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: Karen Vanmeer | Statement: [Boom Town, character, Karen Vanmeer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Vanmeer Context triple: [Boom Town, character, Karen Vanmeer]
-
A.
Karen Rosenfelt
Karen Rosenfelt is an American film producer known for her work on major studio franchises and popular young adult adaptations, including entries in the Twilight series.
-
B.
Karen Vogtmann
Karen Vogtmann is an American mathematician known for her influential work in geometric group theory and topology, particularly on Outer space and automorphisms of free groups.
-
C.
Colleen Ahland
Colleen Ahland is a linguist known for her research on the Koman languages of Ethiopia and Sudan, focusing on their documentation, description, and classification.
-
D.
Karen Gunderson
Karen Gunderson is an American singer best known as a member of the folk music group The New Christy Minstrels.
-
E.
Anna Nolin
Anna Nolin is an American educator and school district leader who serves as superintendent of the Newton Public Schools in Massachusetts.
- 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: Karen Vanmeer Triple: [Boom Town, character, Karen Vanmeer]
Generated description
Karen Vanmeer is a fictional character from the Canadian television drama series "Boom Town."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karen Vanmeer Target entity description: Karen Vanmeer is a fictional character from the Canadian television drama series "Boom Town."
-
A.
Karen Rosenfelt
Karen Rosenfelt is an American film producer known for her work on major studio franchises and popular young adult adaptations, including entries in the Twilight series.
-
B.
Karen Vogtmann
Karen Vogtmann is an American mathematician known for her influential work in geometric group theory and topology, particularly on Outer space and automorphisms of free groups.
-
C.
Colleen Ahland
Colleen Ahland is a linguist known for her research on the Koman languages of Ethiopia and Sudan, focusing on their documentation, description, and classification.
-
D.
Karen Gunderson
Karen Gunderson is an American singer best known as a member of the folk music group The New Christy Minstrels.
-
E.
Anna Nolin
Anna Nolin is an American educator and school district leader who serves as superintendent of the Newton Public Schools in Massachusetts.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb95223e081908b2954769d2f46c8 |
completed | March 8, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53fd1a2088190b43cded6c0e90633 |
completed | March 14, 2026, 11 a.m. |
| NEDg | Description generation | batch_69b5414ed2b4819095f20d96e301a7b2 |
completed | March 14, 2026, 11:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b541a55cb081909ec1f87a7553b6f2 |
completed | March 14, 2026, 11:08 a.m. |
Created at: March 8, 2026, 3:15 p.m.