Triple
T22765354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambertseter |
E563108
|
entity |
| Predicate | hasFacility |
P105
|
FINISHED |
| Object |
Lambertseter senter
Lambertseter senter is a shopping mall and commercial center serving the Lambertseter neighborhood in Oslo, Norway.
|
E1531838
|
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: Lambertseter senter | Statement: [Lambertseter, hasFacility, Lambertseter senter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lambertseter senter Context triple: [Lambertseter, hasFacility, Lambertseter senter]
-
A.
Lambertseter
Lambertseter is a residential borough in Oslo, Norway, known as one of the country’s first planned suburban housing areas with extensive post-war apartment developments.
-
B.
Lambertseter station
Lambertseter station is a metro station on the Oslo Metro system in Norway, serving the Lambertseter neighborhood.
-
C.
Sæter
Sæter is a residential and commercial neighborhood in the Nordstrand borough of Oslo, Norway, known for its local center with shops, services, and public transport connections.
-
D.
Lyngseidet
Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
-
E.
Smestad
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
- 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: Lambertseter senter Triple: [Lambertseter, hasFacility, Lambertseter senter]
Generated description
Lambertseter senter is a shopping mall and commercial center serving the Lambertseter neighborhood in Oslo, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lambertseter senter Target entity description: Lambertseter senter is a shopping mall and commercial center serving the Lambertseter neighborhood in Oslo, Norway.
-
A.
Lambertseter
chosen
Lambertseter is a residential borough in Oslo, Norway, known as one of the country’s first planned suburban housing areas with extensive post-war apartment developments.
-
B.
Lambertseter station
Lambertseter station is a metro station on the Oslo Metro system in Norway, serving the Lambertseter neighborhood.
-
C.
Sæter
Sæter is a residential and commercial neighborhood in the Nordstrand borough of Oslo, Norway, known for its local center with shops, services, and public transport connections.
-
D.
Lyngseidet
Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
-
E.
Smestad
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
- F. None of above.
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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a80249c819091569e7b8d500b45 |
completed | April 29, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b981d46788190a6ba2d605d82c036 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b99d055888190844bb88f0ba1e253 |
completed | May 18, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9a46b4fc81909bae1dfdd7d825ab |
completed | May 18, 2026, 11:01 p.m. |
Created at: April 17, 2026, 3:26 p.m.