Triple
T13949165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Gade |
E335471
|
entity |
| Predicate | hasValleyName |
P650
|
FINISHED |
| Object | Gade Valley |
E1100124
|
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: Gade Valley | Statement: [River Gade, hasValleyName, Gade Valley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gade Valley Context triple: [River Gade, hasValleyName, Gade Valley]
-
A.
Gade Valley
chosen
Gade Valley is a low-lying valley landscape in Hertfordshire, England, shaped by the River Gade and its surrounding floodplain.
-
B.
Verdal valley
Verdal valley is a fertile agricultural valley in Trøndelag county, central Norway, known for its farming landscape and the town of Verdalsøra.
-
C.
Skjåk valley
Skjåk valley is a scenic valley in Innlandet county, Norway, known for its mountainous landscapes, traditional farming, and proximity to major national parks like Jotunheimen and Reinheimen.
-
D.
Groruddalen
Groruddalen is a large valley and suburban area in the northeastern part of Oslo, Norway, known for its diverse population and extensive residential neighborhoods.
-
E.
Saudafjorden valley
Saudafjorden valley is a scenic fjord valley in western Norway known for its steep mountainsides, deep waters, and proximity to the industrial town of Sauda.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e12171c8190b95746bdd4845def |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d72a17c8190b63f9f441731917d |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 9, 2026, 10:17 p.m.