Triple
T10429017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lunner |
E245859
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Roa
Roa is the administrative center and largest settlement of Lunner municipality in Viken county, Norway.
|
E862878
|
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: Roa | Statement: [Lunner, capital, Roa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roa Context triple: [Lunner, capital, Roa]
-
A.
Roa
Roa is a historic town in the province of Burgos, Spain, known for its medieval heritage and location in the Ribera del Duero wine region.
-
B.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
C.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
-
D.
Moura
Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
-
E.
Ráquira
Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
- 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: Roa Triple: [Lunner, capital, Roa]
Generated description
Roa is the administrative center and largest settlement of Lunner municipality in Viken county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roa Target entity description: Roa is the administrative center and largest settlement of Lunner municipality in Viken county, Norway.
-
A.
Roa
Roa is a historic town in the province of Burgos, Spain, known for its medieval heritage and location in the Ribera del Duero wine region.
-
B.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
C.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
-
D.
Moura
Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
-
E.
Ráquira
Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
- 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_69d4ea4b4b5881908ae23f8efeea482b |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ea554888190bf2ef31e33c0ff14 |
completed | April 10, 2026, 4:37 a.m. |
| NEDg | Description generation | batch_69d8837e70508190b03e8983b2617eac |
completed | April 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d889cc40648190a1d80b955e676ea5 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 6, 2026, 12:13 p.m.