Triple
T3947601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mönch |
E92183
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Eiger |
E118572
|
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: Eiger | Statement: [Mönch, near, Eiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eiger Context triple: [Mönch, near, Eiger]
-
A.
Eiger
chosen
Eiger is a famous and formidable mountain in the Swiss Alps, renowned for its steep and challenging north face that has long attracted and tested mountaineers.
-
B.
Matterhorn
The Matterhorn is a famous pyramidal Alpine peak on the border between Switzerland and Italy, renowned for its striking shape and prominence in mountaineering history.
-
C.
Jungfrau
Jungfrau is a prominent and picturesque mountain peak in the Swiss Alps, renowned for its dramatic scenery and status as part of a UNESCO World Heritage Site.
-
D.
Skil Brum
Skil Brum is a high, remote mountain peak in the Karakoram range of the Himalayas, known primarily to mountaineers for its challenging climbing conditions and proximity to K2.
-
E.
Aiguille du Dru
Aiguille du Dru is a striking granite peak in the Mont Blanc massif of the French Alps, famed among climbers for its steep faces and challenging routes.
- 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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef0db56cc8190a5303e8fe0efbfc2 |
completed | March 9, 2026, 4:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5339bc5d481909e750873d65fff4c |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:24 p.m.