Triple
T18597490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus South district |
E454529
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Hasselager
Hasselager is a residential neighborhood in the southern part of Aarhus, Denmark.
|
E1333043
|
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: Hasselager | Statement: [Aarhus South district, hasNeighborhood, Hasselager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasselager Context triple: [Aarhus South district, hasNeighborhood, Hasselager]
-
A.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
B.
Hassela
Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
-
C.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
D.
Haslum
Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
-
E.
Blokhus
Blokhus is a Danish seaside resort town known for its wide sandy beaches, coastal dunes, and tourism along the North Sea.
- 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: Hasselager Triple: [Aarhus South district, hasNeighborhood, Hasselager]
Generated description
Hasselager is a residential neighborhood in the southern part of Aarhus, Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hasselager Target entity description: Hasselager is a residential neighborhood in the southern part of Aarhus, Denmark.
-
A.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
B.
Hassela
Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
-
C.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
D.
Haslum
Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
-
E.
Blokhus
Blokhus is a Danish seaside resort town known for its wide sandy beaches, coastal dunes, and tourism along the North Sea.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474d934481909b4afd5ef9031c73 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05037eda788190977fcb50aa4d2357 |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a0504cd76388190b67c78250297573d |
completed | May 13, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505482c588190952fe07726f64b93 |
completed | May 13, 2026, 11:12 p.m. |
Created at: April 10, 2026, 11:44 a.m.