Triple
T15528962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moldeelva |
E370158
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Moldeelva (Norwegian) |
E370158
|
NE FINISHED |
How this triple was built (2 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: Moldeelva (Norwegian) | Statement: [Moldeelva, hasNameInLanguage, Moldeelva (Norwegian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moldeelva (Norwegian) Context triple: [Moldeelva, hasNameInLanguage, Moldeelva (Norwegian)]
-
A.
Moldeelva
chosen
Moldeelva is a river flowing through the Norwegian town of Molde, contributing to its landscape and local environment.
-
B.
Målselva
Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
-
C.
Vangsmjøse
Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
-
D.
Verdalselva
Verdalselva is a river in Trøndelag county, Norway, known for flowing through the Verdalen valley and supporting local agriculture, recreation, and salmon fishing.
-
E.
Steinsdalselva
Steinsdalselva is a river in the municipality of Kvam in Vestland county, western Norway, known for flowing through a scenic valley landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414620588190958ffde651ccab5f |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5b989c8190a76612df167ba1dd |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:05 a.m.