Triple
T831352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trøndelag |
E17971
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
|
E129647
|
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: Verdal | Statement: [Trøndelag, contains, Verdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verdal Context triple: [Trøndelag, contains, Verdal]
-
A.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
B.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
C.
Hallingdal
Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
-
D.
Numedal
Numedal is a valley in southeastern Norway known for its traditional wooden architecture, medieval stave churches, and scenic river landscape.
-
E.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
- 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: Verdal Triple: [Trøndelag, contains, Verdal]
Generated description
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verdal Target entity description: Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
A.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
B.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
C.
Hallingdal
Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
-
D.
Numedal
Numedal is a valley in southeastern Norway known for its traditional wooden architecture, medieval stave churches, and scenic river landscape.
-
E.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb4be948190ae757df85bdc40e4 |
completed | March 1, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac598e6ccc8190b0d75d36036f5e42 |
completed | March 7, 2026, 4:59 p.m. |
| NEDg | Description generation | batch_69ac5a8b342881909b11d86270717d72 |
completed | March 7, 2026, 5:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5af24a948190a37c832508149a48 |
completed | March 7, 2026, 5:05 p.m. |
Created at: March 1, 2026, 7:38 p.m.