Triple
T15029756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johan Tobias Sergel |
E378312
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sergel
Sergel is a Swedish surname most notably associated with the 18th-century sculptor Johan Tobias Sergel.
|
E1134005
|
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: Sergel | Statement: [Johan Tobias Sergel, familyName, Sergel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sergel Context triple: [Johan Tobias Sergel, familyName, Sergel]
-
A.
SF Sergel
SF Sergel was a major central Stockholm cinema complex, later rebranded as Filmstaden Sergel, known for showing mainstream and blockbuster films.
-
B.
George Englund
George Englund was an American film editor, director, and producer known for works like "The Ugly American" and for his long marriage to actress Cloris Leachman.
-
C.
Sven Berg
Sven Berg is an architect best known for his work on the design of the Oklahoma City National Memorial.
-
D.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
-
E.
Åkerman
Åkerman is a Swedish surname most notably borne by Canadian-Swedish actress and model Malin Åkerman.
- 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: Sergel Triple: [Johan Tobias Sergel, familyName, Sergel]
Generated description
Sergel is a Swedish surname most notably associated with the 18th-century sculptor Johan Tobias Sergel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sergel Target entity description: Sergel is a Swedish surname most notably associated with the 18th-century sculptor Johan Tobias Sergel.
-
A.
SF Sergel
SF Sergel was a major central Stockholm cinema complex, later rebranded as Filmstaden Sergel, known for showing mainstream and blockbuster films.
-
B.
George Englund
George Englund was an American film editor, director, and producer known for works like "The Ugly American" and for his long marriage to actress Cloris Leachman.
-
C.
Sven Berg
Sven Berg is an architect best known for his work on the design of the Oklahoma City National Memorial.
-
D.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
-
E.
Åkerman
Åkerman is a Swedish surname most notably borne by Canadian-Swedish actress and model Malin Åkerman.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd967588190821cf47e9734db21 |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9e5dbbe0819084567688758b0245 |
completed | May 9, 2026, 2:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9eedca1481908ce438991184d62e |
completed | May 9, 2026, 2:41 a.m. |
Created at: April 10, 2026, 2:59 a.m.