Triple

T5790639
Position Surface form Disambiguated ID Type / Status
Subject Gamle Oslo E128382 entity
Predicate containsNeighbourhood P4813 FINISHED
Object Loenga
Loenga is a small residential and industrial neighborhood in Oslo, Norway, situated near the railway yards and the Oslofjord.
 E551252 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: Loenga | Statement: [Gamle Oslo, containsNeighbourhood, Loenga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Loenga
Context triple: [Gamle Oslo, containsNeighbourhood, Loenga]
  • A. Talanga
    Talanga is a town and municipality in central Honduras known for its agricultural activities and location along the highway connecting Tegucigalpa with the country's northern regions.
  • B. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • C. Lilangeni
    The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • D. Kalanga
    Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • 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: Loenga
Triple: [Gamle Oslo, containsNeighbourhood, Loenga]
Generated description
Loenga is a small residential and industrial neighborhood in Oslo, Norway, situated near the railway yards and the Oslofjord.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Loenga
Target entity description: Loenga is a small residential and industrial neighborhood in Oslo, Norway, situated near the railway yards and the Oslofjord.
  • A. Talanga
    Talanga is a town and municipality in central Honduras known for its agricultural activities and location along the highway connecting Tegucigalpa with the country's northern regions.
  • B. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • C. Lilangeni
    The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • D. Kalanga
    Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5585788190821b8da40259e0e7 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a178ccf481909beddf56b66a588d completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a2463cb08190aa5976ebd62c30d6 completed March 23, 2026, 2:15 a.m.
NED2 Entity disambiguation (via description) batch_69c0a2afcef88190a77c8089a1b85393 completed March 23, 2026, 2:17 a.m.
Created at: March 22, 2026, 3:51 p.m.