Triple
T7482722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Göran Persson |
E176800
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Hans Göran
Hans Göran is the given first name of Göran Persson, the former Prime Minister of Sweden.
|
E668419
|
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: Hans Göran | Statement: [Göran Persson, givenName, Hans Göran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hans Göran Context triple: [Göran Persson, givenName, Hans Göran]
-
A.
Göran Månsson
Göran Månsson is a Swedish architect best known for designing Stockholm’s renowned Vasa Museum, which houses the 17th-century warship Vasa.
-
B.
Torgny Segerstedt
Torgny Segerstedt was a Swedish philosopher and academic leader best known for serving as rector of Uppsala University and for his influence on higher education in Sweden.
-
C.
Göran Gustafsson
Göran Gustafsson was a Swedish entrepreneur and philanthropist known for his significant contributions to scientific research funding.
-
D.
Östen Undén
Östen Undén was a Swedish Social Democratic politician, legal scholar, and long-serving foreign minister who briefly served as acting Prime Minister of Sweden during the 1940s.
-
E.
Torgny Lindgren
Torgny Lindgren was a renowned Swedish author and member of the Swedish Academy, celebrated for his novels and short stories often set in rural Västerbotten.
- 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: Hans Göran Triple: [Göran Persson, givenName, Hans Göran]
Generated description
Hans Göran is the given first name of Göran Persson, the former Prime Minister of Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hans Göran Target entity description: Hans Göran is the given first name of Göran Persson, the former Prime Minister of Sweden.
-
A.
Göran Månsson
Göran Månsson is a Swedish architect best known for designing Stockholm’s renowned Vasa Museum, which houses the 17th-century warship Vasa.
-
B.
Torgny Segerstedt
Torgny Segerstedt was a Swedish philosopher and academic leader best known for serving as rector of Uppsala University and for his influence on higher education in Sweden.
-
C.
Göran Gustafsson
Göran Gustafsson was a Swedish entrepreneur and philanthropist known for his significant contributions to scientific research funding.
-
D.
Östen Undén
Östen Undén was a Swedish Social Democratic politician, legal scholar, and long-serving foreign minister who briefly served as acting Prime Minister of Sweden during the 1940s.
-
E.
Torgny Lindgren
Torgny Lindgren was a renowned Swedish author and member of the Swedish Academy, celebrated for his novels and short stories often set in rural Västerbotten.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5374bb08190bdf6ca72a3d0cd1c |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c68bcf081908a2c280152d887f0 |
completed | March 28, 2026, 8:39 p.m. |
| NEDg | Description generation | batch_69c83ddda5688190be1ec69f23671f60 |
completed | March 28, 2026, 8:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83e42b0048190b1abd8ae99c97e38 |
completed | March 28, 2026, 8:46 p.m. |
Created at: March 27, 2026, 3:42 p.m.