Triple
T10445354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | province of Östergötland |
E246271
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Mjölby
Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
|
E864236
|
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: Mjölby | Statement: [province of Östergötland, hasTown, Mjölby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mjölby Context triple: [province of Östergötland, hasTown, Mjölby]
-
A.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Ljungby
Ljungby is a small Swedish town in southern Småland known for its lakeside surroundings, forestry-based economy, and role as a local commercial and cultural center.
-
E.
Mörbylånga
Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
- 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: Mjölby Triple: [province of Östergötland, hasTown, Mjölby]
Generated description
Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mjölby Target entity description: Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
-
A.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Ljungby
Ljungby is a small Swedish town in southern Småland known for its lakeside surroundings, forestry-based economy, and role as a local commercial and cultural center.
-
E.
Mörbylånga
Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbf81508190a160edea85105d3a |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87eeae8788190b63534fa4f942ead |
completed | April 10, 2026, 4:39 a.m. |
| NEDg | Description generation | batch_69d886c3fdcc8190a67a7f7788b8a2e8 |
completed | April 10, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d88dc15ab481909011c5de93bbab14 |
completed | April 10, 2026, 5:42 a.m. |
Created at: April 6, 2026, 12:16 p.m.