Triple
T3701544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harstad |
E78588
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object |
Ibestad
Ibestad is a small island-based municipality in Troms og Finnmark county in northern Norway, known for its rugged coastal landscape and fishing communities.
|
E382080
|
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: Ibestad | Statement: [Harstad, hasNeighbouringMunicipality, Ibestad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ibestad Context triple: [Harstad, hasNeighbouringMunicipality, Ibestad]
-
A.
Grebbestad
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
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.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
D.
Rakkestad
Rakkestad is a rural municipality in Viken county, southeastern Norway, known for its agriculture and forests.
-
E.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
- 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: Ibestad Triple: [Harstad, hasNeighbouringMunicipality, Ibestad]
Generated description
Ibestad is a small island-based municipality in Troms og Finnmark county in northern Norway, known for its rugged coastal landscape and fishing communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ibestad Target entity description: Ibestad is a small island-based municipality in Troms og Finnmark county in northern Norway, known for its rugged coastal landscape and fishing communities.
-
A.
Grebbestad
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
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.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
D.
Rakkestad
Rakkestad is a rural municipality in Viken county, southeastern Norway, known for its agriculture and forests.
-
E.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdf1b16081909b18af630d0b4817 |
completed | March 14, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69b4d1a5411c81909f464f8abc012177 |
completed | March 14, 2026, 3:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4d20a7fa8819093e8e66ba9272f31 |
completed | March 14, 2026, 3:12 a.m. |
Created at: March 8, 2026, 3:26 p.m.