Triple
T6142485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trondheim |
E136993
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Munkholmen
Munkholmen is a small historic island off Trondheim, Norway, known for its past roles as a monastery, fortress, prison, and World War II defensive site, and today as a popular tourist destination.
|
E570932
|
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: Munkholmen | Statement: [Trondheim, hasLandmark, Munkholmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Munkholmen Context triple: [Trondheim, hasLandmark, Munkholmen]
-
A.
Kastellholmen
Kastellholmen is a small island in central Stockholm, Sweden, known for its historic red-brick citadel and scenic waterfront views.
-
B.
Skärholmen
Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
-
C.
Storholmen
Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
-
D.
Stadsholmen
Stadsholmen is the central island in Stockholm’s historic Gamla stan (Old Town), known for its medieval street layout and well-preserved architecture.
-
E.
Skeppsholmen
Skeppsholmen is a small central Stockholm island known for its historic naval heritage, museums, and scenic waterfront views.
- 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: Munkholmen Triple: [Trondheim, hasLandmark, Munkholmen]
Generated description
Munkholmen is a small historic island off Trondheim, Norway, known for its past roles as a monastery, fortress, prison, and World War II defensive site, and today as a popular tourist destination.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Munkholmen Target entity description: Munkholmen is a small historic island off Trondheim, Norway, known for its past roles as a monastery, fortress, prison, and World War II defensive site, and today as a popular tourist destination.
-
A.
Kastellholmen
Kastellholmen is a small island in central Stockholm, Sweden, known for its historic red-brick citadel and scenic waterfront views.
-
B.
Skärholmen
Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
-
C.
Storholmen
Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
-
D.
Stadsholmen
Stadsholmen is the central island in Stockholm’s historic Gamla stan (Old Town), known for its medieval street layout and well-preserved architecture.
-
E.
Skeppsholmen
Skeppsholmen is a small central Stockholm island known for its historic naval heritage, museums, and scenic waterfront views.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb387ac8190a60579b59a741425 |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135f2defc8190a666f82e230a51c2 |
completed | March 23, 2026, 12:45 p.m. |
| NEDg | Description generation | batch_69c13679dd58819099036d1119fa370b |
completed | March 23, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1376db6a0819087c0d0aebc2e2b3e |
completed | March 23, 2026, 12:51 p.m. |
Created at: March 22, 2026, 4:16 p.m.