Triple
T3166539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kari Lehtonen |
E66224
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lehtonen
Lehtonen is a Finnish surname most notably associated with former NHL goaltender Kari Lehtonen.
|
E334003
|
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: Lehtonen | Statement: [Kari Lehtonen, familyName, Lehtonen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lehtonen Context triple: [Kari Lehtonen, familyName, Lehtonen]
-
A.
Kukkonen
Kukkonen is a Finnish surname most notably associated with Greta Kukkonen, the first wife of U.S. President Ronald Reagan.
-
B.
Jere Lehtinen
Jere Lehtinen is a Finnish former NHL winger for the Dallas Stars, renowned as one of the league’s elite defensive forwards and a multiple-time Frank J. Selke Trophy winner.
-
C.
Tatu Ylönen
Tatu Ylönen is a Finnish computer scientist and entrepreneur best known for creating the Secure Shell (SSH) protocol and founding SSH Communications Security.
-
D.
Kauniainen
Kauniainen is a small, affluent town and municipality in southern Finland, completely surrounded by the city of Espoo and known for its high standard of living.
-
E.
Selke
The Selke is a river in central Germany that flows through the Harz Mountains and Saxony-Anhalt, known for its scenic valleys and historic towns along its course.
- 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: Lehtonen Triple: [Kari Lehtonen, familyName, Lehtonen]
Generated description
Lehtonen is a Finnish surname most notably associated with former NHL goaltender Kari Lehtonen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lehtonen Target entity description: Lehtonen is a Finnish surname most notably associated with former NHL goaltender Kari Lehtonen.
-
A.
Kukkonen
Kukkonen is a Finnish surname most notably associated with Greta Kukkonen, the first wife of U.S. President Ronald Reagan.
-
B.
Jere Lehtinen
Jere Lehtinen is a Finnish former NHL winger for the Dallas Stars, renowned as one of the league’s elite defensive forwards and a multiple-time Frank J. Selke Trophy winner.
-
C.
Tatu Ylönen
Tatu Ylönen is a Finnish computer scientist and entrepreneur best known for creating the Secure Shell (SSH) protocol and founding SSH Communications Security.
-
D.
Kauniainen
Kauniainen is a small, affluent town and municipality in southern Finland, completely surrounded by the city of Espoo and known for its high standard of living.
-
E.
Selke
The Selke is a river in central Germany that flows through the Harz Mountains and Saxony-Anhalt, known for its scenic valleys and historic towns along its course.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada643e3e481908f4526d66e36e150 |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235e108cc81909d5733bd00cb0bee |
completed | March 12, 2026, 3:41 a.m. |
| NEDg | Description generation | batch_69b2372a54a481908a4a954b8986aad7 |
completed | March 12, 2026, 3:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b23806a3c8819096069982b3612730 |
completed | March 12, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:06 p.m.