Triple
T4298472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saas-Fee |
E99773
|
entity |
| Predicate | surroundedBy |
P224
|
FINISHED |
| Object | Nadelhorn |
E164505
|
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: Nadelhorn | Statement: [Saas-Fee, surroundedBy, Nadelhorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nadelhorn Context triple: [Saas-Fee, surroundedBy, Nadelhorn]
-
A.
Nadelhorn
chosen
Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing routes.
-
B.
Fletschhorn
Fletschhorn is a prominent mountain peak in the Swiss Pennine Alps, known for its glaciated slopes and popularity among alpine climbers.
-
C.
Rimpfischhorn
Rimpfischhorn is a prominent high-altitude mountain in the Swiss Pennine Alps, known for its glaciated slopes and challenging climbing routes.
-
D.
Grauspitz
Grauspitz is a prominent alpine peak in the Rätikon range of the Alps, known as the highest mountain in Liechtenstein and shared with Switzerland.
-
E.
Wilseder Berg
Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509d39348190aa83304661230cba |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f5b965c48190990357f4cb4e30cb |
completed | March 14, 2026, 11:56 p.m. |
Created at: March 12, 2026, 11:08 p.m.