Triple
T5625119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagginhorn |
E147698
|
entity |
| Predicate | hasNearbyPeak |
P7612
|
FINISHED |
| Object | Fletschhorn |
E158906
|
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: Fletschhorn | Statement: [Lagginhorn, hasNearbyPeak, Fletschhorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fletschhorn Context triple: [Lagginhorn, hasNearbyPeak, Fletschhorn]
-
A.
Fletschhorn
chosen
Fletschhorn is a prominent mountain peak in the Swiss Pennine Alps, known for its glaciated slopes and popularity among alpine climbers.
-
B.
Wiesbachhorn
Wiesbachhorn is a prominent alpine peak in the Austrian Alps, known for its impressive height and glaciated slopes within the Hohe Tauern range.
-
C.
Stecknadelhorn
Stecknadelhorn is a high alpine peak in the Pennine Alps of Switzerland, known as one of the prominent summits of the Mischabel range.
-
D.
Hösthorn
Hösthorn is a poetry collection by Swedish Nobel laureate Erik Axel Karlfeldt, known for its evocative depictions of nature and rural life.
-
E.
Schnebelhorn
Schnebelhorn is a prominent mountain in northeastern Switzerland known as the highest peak in the canton of Zürich and a popular destination for hiking and nature excursions.
- 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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02235b4e48190a529f70605bf47ca |
completed | March 22, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c24381aff48190980ada94ee95593e |
completed | March 24, 2026, 7:55 a.m. |
Created at: March 22, 2026, 3:40 p.m.