Triple
T15014410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romsdal |
E377920
|
entity |
| Predicate | containsMountain |
P10602
|
FINISHED |
| Object |
Moldemarka
Moldemarka is a popular forested recreational area and hiking terrain near the town of Molde in Norway’s Romsdal region.
|
E1132489
|
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: Moldemarka | Statement: [Romsdal, containsMountain, Moldemarka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moldemarka Context triple: [Romsdal, containsMountain, Moldemarka]
-
A.
Mossemarka
Mossemarka is a forested recreational area near the town of Moss in southeastern Norway, popular for outdoor activities such as hiking and skiing.
-
B.
Moldanubicum
Moldanubicum is a major geological unit in Central Europe characterized by ancient metamorphic and igneous rocks that form part of the Bohemian Massif.
-
C.
Mora
Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
-
D.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
E.
Mora
Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
- 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: Moldemarka Triple: [Romsdal, containsMountain, Moldemarka]
Generated description
Moldemarka is a popular forested recreational area and hiking terrain near the town of Molde in Norway’s Romsdal region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Moldemarka Target entity description: Moldemarka is a popular forested recreational area and hiking terrain near the town of Molde in Norway’s Romsdal region.
-
A.
Mossemarka
Mossemarka is a forested recreational area near the town of Moss in southeastern Norway, popular for outdoor activities such as hiking and skiing.
-
B.
Moldanubicum
Moldanubicum is a major geological unit in Central Europe characterized by ancient metamorphic and igneous rocks that form part of the Bohemian Massif.
-
C.
Mora
Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
-
D.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
E.
Mora
Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7623c3c819092ca36b358b01842 |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe96aa3c888190a65e7b3c3b130131 |
completed | May 9, 2026, 2:06 a.m. |
| NEDg | Description generation | batch_69fe97af0a0c8190bca3ea103d05fd99 |
completed | May 9, 2026, 2:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe98b18ab48190b2a47418904e6643 |
completed | May 9, 2026, 2:15 a.m. |
Created at: April 10, 2026, 2:55 a.m.