Triple
T1073461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bornholm |
E23381
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Aakirkeby
Aakirkeby is a small historic town on the Danish island of Bornholm, known for its medieval church and role as a local commercial and cultural center.
|
E127860
|
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: Aakirkeby | Statement: [Bornholm, hasTown, Aakirkeby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aakirkeby Context triple: [Bornholm, hasTown, Aakirkeby]
-
A.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
B.
Ullensaker
Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
-
C.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
D.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
E.
Djursholm
Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
- 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: Aakirkeby Triple: [Bornholm, hasTown, Aakirkeby]
Generated description
Aakirkeby is a small historic town on the Danish island of Bornholm, known for its medieval church and role as a local commercial and cultural center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aakirkeby Target entity description: Aakirkeby is a small historic town on the Danish island of Bornholm, known for its medieval church and role as a local commercial and cultural center.
-
A.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
B.
Ullensaker
Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
-
C.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
D.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
E.
Djursholm
Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92afad88190b7705923f71fc760 |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac538a5d248190bb44c6b27d2c714c |
completed | March 7, 2026, 4:34 p.m. |
| NEDg | Description generation | batch_69ac541f80208190bf23aad6a21515bd |
completed | March 7, 2026, 4:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac548b363881908de3588d34c4960c |
completed | March 7, 2026, 4:38 p.m. |
Created at: March 1, 2026, 7:42 p.m.