Triple
T1510298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uppsala University |
E30374
|
entity |
| Predicate | hasNotableAlumnus |
P51
|
FINISHED |
| Object |
Lena Ek
Lena Ek is a Swedish Centre Party politician and former Minister for the Environment in Sweden.
|
E174117
|
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: Lena Ek | Statement: [Uppsala University, hasNotableAlumnus, Lena Ek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lena Ek Context triple: [Uppsala University, hasNotableAlumnus, Lena Ek]
-
A.
Lena
Lena is an alternate given name of Lee Krasner, the influential American abstract expressionist painter and wife of Jackson Pollock.
-
B.
Sara Esberg
Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
-
C.
Nina Agdal
Nina Agdal is a Danish fashion model best known for her work with Sports Illustrated Swimsuit Issue and major international advertising campaigns.
-
D.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
-
E.
Lena Gieseke
Lena Gieseke is a German visual effects artist and academic known for her work in 3D animation and digital media.
- 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: Lena Ek Triple: [Uppsala University, hasNotableAlumnus, Lena Ek]
Generated description
Lena Ek is a Swedish Centre Party politician and former Minister for the Environment in Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lena Ek Target entity description: Lena Ek is a Swedish Centre Party politician and former Minister for the Environment in Sweden.
-
A.
Lena
Lena is an alternate given name of Lee Krasner, the influential American abstract expressionist painter and wife of Jackson Pollock.
-
B.
Sara Esberg
Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
-
C.
Nina Agdal
Nina Agdal is a Danish fashion model best known for her work with Sports Illustrated Swimsuit Issue and major international advertising campaigns.
-
D.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
-
E.
Lena Gieseke
Lena Gieseke is a German visual effects artist and academic known for her work in 3D animation and digital media.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907d4edd48190a03c85e1a0cc02b1 |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad294805308190ada3ed69ec71ce43 |
completed | March 8, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69ad2a1742d48190a82c1fc8c81d5c21 |
completed | March 8, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2a9e50888190bab83785f11135ea |
completed | March 8, 2026, 7:51 a.m. |
Created at: March 4, 2026, 7:26 p.m.