Triple
T18702239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlsson på taket |
E457280
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object |
Lillebror
Lillebror is the young boy protagonist who befriends the mischievous flying man Karlsson in Astrid Lindgren’s beloved children’s stories.
|
E1338237
|
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: Lillebror | Statement: [Carlsson på taket, associatedWithCharacter, Lillebror]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lillebror Context triple: [Carlsson på taket, associatedWithCharacter, Lillebror]
-
A.
Lillestrøm
Lillestrøm is a Norwegian town and former municipality in the Greater Oslo Region, known as a regional commercial center and transport hub.
-
B.
Hellemmes-Lille
Hellemmes-Lille is a former independent commune now functioning as an associated district of the city of Lille in northern France.
-
C.
Mellerud
Mellerud is a small town in western Sweden known for its location by Lake Vänern and its role as a local service and transport hub.
-
D.
Örgryte IS
Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
-
E.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
- 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: Lillebror Triple: [Carlsson på taket, associatedWithCharacter, Lillebror]
Generated description
Lillebror is the young boy protagonist who befriends the mischievous flying man Karlsson in Astrid Lindgren’s beloved children’s stories.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lillebror Target entity description: Lillebror is the young boy protagonist who befriends the mischievous flying man Karlsson in Astrid Lindgren’s beloved children’s stories.
-
A.
Lillestrøm
Lillestrøm is a Norwegian town and former municipality in the Greater Oslo Region, known as a regional commercial center and transport hub.
-
B.
Hellemmes-Lille
Hellemmes-Lille is a former independent commune now functioning as an associated district of the city of Lille in northern France.
-
C.
Mellerud
Mellerud is a small town in western Sweden known for its location by Lake Vänern and its role as a local service and transport hub.
-
D.
Örgryte IS
Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
-
E.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56714d0588190ac050356bc2784fd |
completed | April 19, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b36caa88190a6302741aca9eb00 |
completed | May 14, 2026, 1:53 a.m. |
| NEDg | Description generation | batch_6a052bb371b88190a632f39c891df93b |
completed | May 14, 2026, 1:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052c7532588190bcc3e2f15fef253a |
completed | May 14, 2026, 1:59 a.m. |
Created at: April 10, 2026, 11:49 a.m.