Triple
T7007036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rimpfischhorn |
E162481
|
entity |
| Predicate | overlooks |
P1323
|
FINISHED |
| Object | Matter Valley |
E534241
|
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: Matter Valley | Statement: [Rimpfischhorn, overlooks, Matter Valley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matter Valley Context triple: [Rimpfischhorn, overlooks, Matter Valley]
-
A.
Matter valley
chosen
Matter valley is a high alpine valley in the Swiss canton of Valais, known for its dramatic peaks and popular mountaineering and skiing destinations such as Zermatt.
-
B.
Chemical Valley
Chemical Valley is a major industrial area in Sarnia, Ontario, characterized by a dense concentration of petrochemical and chemical manufacturing facilities.
-
C.
Deep Valley
Deep Valley is a 1947 American drama film in which Anne Revere delivered one of her notable screen performances.
-
D.
Lore Valley
Lore Valley is a region where the Bada language is natively spoken, forming a key part of the language’s cultural and geographic heartland.
-
E.
Mattersey
Mattersey is a small village and civil parish in Nottinghamshire, England, known for its rural setting and historic priory remains.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc35cb848190a839919021efce81 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a43c3a081909b9150d36ba107f5 |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.