Triple
T6216542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogaland |
E139000
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Hå
Hå is a coastal municipality in southwestern Norway known for its agricultural landscape, beaches, and location along the North Sea in Rogaland county.
|
E577058
|
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: Hå | Statement: [Rogaland, hasMunicipality, Hå]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hå Context triple: [Rogaland, hasMunicipality, Hå]
-
A.
Hareid
Hareid is a coastal village and municipality in western Norway known for its maritime industries and scenic fjord landscape.
-
B.
Hasle
Hasle is a small coastal town on the Danish island of Bornholm, known for its historic harbor, smoked herring, and scenic Baltic Sea surroundings.
-
C.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
D.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
E.
Hakstol
Hakstol is a surname most notably associated with Dave Hakstol, a Canadian professional ice hockey coach.
- 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: Hå Triple: [Rogaland, hasMunicipality, Hå]
Generated description
Hå is a coastal municipality in southwestern Norway known for its agricultural landscape, beaches, and location along the North Sea in Rogaland county.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hå Target entity description: Hå is a coastal municipality in southwestern Norway known for its agricultural landscape, beaches, and location along the North Sea in Rogaland county.
-
A.
Hareid
Hareid is a coastal village and municipality in western Norway known for its maritime industries and scenic fjord landscape.
-
B.
Hasle
Hasle is a small coastal town on the Danish island of Bornholm, known for its historic harbor, smoked herring, and scenic Baltic Sea surroundings.
-
C.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
D.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
E.
Hakstol
Hakstol is a surname most notably associated with Dave Hakstol, a Canadian professional ice hockey coach.
- 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062a1eb3881908c7f735cf9c429ce |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20db4e0ac8190ba7bca1f9d8ac6df |
completed | March 24, 2026, 4:06 a.m. |
| NEDg | Description generation | batch_69c20ff2bb188190baf8a849efc15f87 |
completed | March 24, 2026, 4:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c21365f8f48190970555bd9593b5a4 |
completed | March 24, 2026, 4:30 a.m. |
Created at: March 22, 2026, 4:21 p.m.