Triple
T1229764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finn E. Kydland |
E26409
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Gjesdal
Gjesdal is a municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to the city of Stavanger.
|
E180071
|
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: Gjesdal | Statement: [Finn E. Kydland, placeOfBirth, Gjesdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gjesdal Context triple: [Finn E. Kydland, placeOfBirth, Gjesdal]
-
A.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
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.
Gauldalen
Gauldalen is a river valley and traditional district in central Norway known for its agricultural landscape and the Gaula River running through it.
-
E.
Kjelsås
Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
- 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: Gjesdal Triple: [Finn E. Kydland, placeOfBirth, Gjesdal]
Generated description
Gjesdal is a municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to the city of Stavanger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gjesdal Target entity description: Gjesdal is a municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to the city of Stavanger.
-
A.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
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.
Gauldalen
Gauldalen is a river valley and traditional district in central Norway known for its agricultural landscape and the Gaula River running through it.
-
E.
Kjelsås
Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be3dac2c8190914ff27173bb6b34 |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4682bac88190a25bcc211179296d |
completed | March 8, 2026, 9:50 a.m. |
| NEDg | Description generation | batch_69ad46e8dfa081909db19db6c7349456 |
completed | March 8, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad472da87c8190a5a6ab9504cb81d8 |
completed | March 8, 2026, 9:53 a.m. |
Created at: March 1, 2026, 7:47 p.m.