Triple
T14058382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowy Monaro Regional Council |
E338277
|
entity |
| Predicate | containsLocality |
P45140
|
FINISHED |
| Object |
Bredbo
Bredbo is a small village in New South Wales, Australia, known historically as a coaching stop and for its proximity to the Monaro region’s grazing country.
|
E1078610
|
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: Bredbo | Statement: [Snowy Monaro Regional Council, containsLocality, Bredbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bredbo Context triple: [Snowy Monaro Regional Council, containsLocality, Bredbo]
-
A.
Brynseng
Brynseng is a neighborhood and transport hub in Oslo, Norway, served by the Oslo Metro and other public transit connections.
-
B.
Bolligen
Bolligen is a Swiss municipality in the canton of Bern, known as a residential community on the outskirts of the city of Bern.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Birkenes
Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial 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: Bredbo Triple: [Snowy Monaro Regional Council, containsLocality, Bredbo]
Generated description
Bredbo is a small village in New South Wales, Australia, known historically as a coaching stop and for its proximity to the Monaro region’s grazing country.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bredbo Target entity description: Bredbo is a small village in New South Wales, Australia, known historically as a coaching stop and for its proximity to the Monaro region’s grazing country.
-
A.
Brynseng
Brynseng is a neighborhood and transport hub in Oslo, Norway, served by the Oslo Metro and other public transit connections.
-
B.
Bolligen
Bolligen is a Swiss municipality in the canton of Bern, known as a residential community on the outskirts of the city of Bern.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Birkenes
Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb662c37c8190a629278a97060080 |
completed | May 7, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69fcc99fca8c8190bbcafba5bacfdfda |
completed | May 7, 2026, 5:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcca3a375c819092b3f67612d2ec0c |
completed | May 7, 2026, 5:22 p.m. |
Created at: April 9, 2026, 10:20 p.m.