Triple
T10428165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lier |
E245839
|
entity |
| Predicate | hasAdministrativeCentre |
P1474
|
FINISHED |
| Object |
Lierbyen
Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
|
E862665
|
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: Lierbyen | Statement: [Lier, hasAdministrativeCentre, Lierbyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lierbyen Context triple: [Lier, hasAdministrativeCentre, Lierbyen]
-
A.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
B.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
C.
Lemvig
Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
-
D.
Randaberg
Randaberg is a coastal municipality in Rogaland county, Norway, situated just north of the city of Stavanger and known for its agriculture and scenic shoreline.
-
E.
Bjerke
Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
- 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: Lierbyen Triple: [Lier, hasAdministrativeCentre, Lierbyen]
Generated description
Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lierbyen Target entity description: Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
-
A.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
B.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
C.
Lemvig
Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
-
D.
Randaberg
Randaberg is a coastal municipality in Rogaland county, Norway, situated just north of the city of Stavanger and known for its agriculture and scenic shoreline.
-
E.
Bjerke
Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4a7dcc81909a830e08656a1c0c |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc2b50b48190b1d5b29d19a240c2 |
completed | April 9, 2026, 7:21 p.m. |
| NEDg | Description generation | batch_69d822d76f3481909f7c04be19414b14 |
completed | April 9, 2026, 10:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d859fd8f0c8190b0fec880e1180e50 |
completed | April 10, 2026, 2:01 a.m. |
Created at: April 6, 2026, 12:13 p.m.