Triple
T15220218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alingsås |
E363745
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object |
Mjörn
Mjörn is a lake in western Sweden, known for its scenic surroundings and recreational opportunities near the town of Alingsås.
|
E1147638
|
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: Mjörn | Statement: [Alingsås, hasLake, Mjörn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mjörn Context triple: [Alingsås, hasLake, Mjörn]
-
A.
Järla Sjö
Järla Sjö is a lake and residential area in the eastern suburbs of Stockholm, Sweden, known for its scenic waterfront setting within Nacka.
-
B.
Laxsjön
Laxsjön is a lake in the Swedish province of Dalsland, known for its forested surroundings and opportunities for fishing and outdoor recreation.
-
C.
Svedmyra
Svedmyra is a residential district in southern Stockholm, Sweden, characterized by its apartment blocks, green areas, and proximity to the metro.
-
D.
Storsjön
Storsjön is a large lake in central Sweden, famed for its scenic surroundings and the local legend of the lake monster Storsjöodjuret.
-
E.
Lundevatn
Lundevatn is a lake in Agder county in southern Norway, known for its elongated shape and scenic surroundings.
- 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: Mjörn Triple: [Alingsås, hasLake, Mjörn]
Generated description
Mjörn is a lake in western Sweden, known for its scenic surroundings and recreational opportunities near the town of Alingsås.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mjörn Target entity description: Mjörn is a lake in western Sweden, known for its scenic surroundings and recreational opportunities near the town of Alingsås.
-
A.
Järla Sjö
Järla Sjö is a lake and residential area in the eastern suburbs of Stockholm, Sweden, known for its scenic waterfront setting within Nacka.
-
B.
Laxsjön
Laxsjön is a lake in the Swedish province of Dalsland, known for its forested surroundings and opportunities for fishing and outdoor recreation.
-
C.
Svedmyra
Svedmyra is a residential district in southern Stockholm, Sweden, characterized by its apartment blocks, green areas, and proximity to the metro.
-
D.
Storsjön
Storsjön is a large lake in central Sweden, famed for its scenic surroundings and the local legend of the lake monster Storsjöodjuret.
-
E.
Lundevatn
Lundevatn is a lake in Agder county in southern Norway, known for its elongated shape and scenic surroundings.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007709d3881908384f0fe1e0218d0 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5ebb8d48190b4afc540da8e6a4b |
completed | May 9, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69fee76c54dc8190b6f4231b7f9880b0 |
completed | May 9, 2026, 7:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feeb7fbc9c8190a8d08b03347ed2b2 |
completed | May 9, 2026, 8:08 a.m. |
Created at: April 10, 2026, 3:11 a.m.