Triple
T1275123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennine Alps |
E15796
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Täschhorn
Täschhorn is a prominent 4,491-meter alpine peak in the Swiss canton of Valais, known for its steep faces and challenging climbing routes near the Matterhorn.
|
E186331
|
NE FINISHED |
How this triple was built (4 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: Täschhorn | Statement: [Pennine Alps, contains, Täschhorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Täschhorn Context triple: [Pennine Alps, contains, Täschhorn]
-
A.
Lauteraarhorn
Lauteraarhorn is a prominent, steep pyramidal peak in the Swiss Bernese Alps, known for its challenging climbs and striking glaciated surroundings.
-
B.
Finsteraarhorn
Finsteraarhorn is a prominent, glaciated peak in the Swiss Alps known for its remote location and striking pyramidal shape.
-
C.
Aletschhorn
Aletschhorn is a prominent high peak in the Swiss Alps known for its extensive glaciation and challenging alpine climbs.
-
D.
Dufourspitze
Dufourspitze is the highest peak of the Monte Rosa massif in the Pennine Alps and the second-highest mountain in the Alps and Western Europe.
-
E.
Schreckhorn
Schreckhorn is a prominent and rugged mountain peak in the Swiss Alps, known for its challenging climbs and striking glaciated scenery.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Täschhorn Triple: [Pennine Alps, contains, Täschhorn]
Generated description
Täschhorn is a prominent 4,491-meter alpine peak in the Swiss canton of Valais, known for its steep faces and challenging climbing routes near the Matterhorn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Täschhorn Target entity description: Täschhorn is a prominent 4,491-meter alpine peak in the Swiss canton of Valais, known for its steep faces and challenging climbing routes near the Matterhorn.
-
A.
Lauteraarhorn
Lauteraarhorn is a prominent, steep pyramidal peak in the Swiss Bernese Alps, known for its challenging climbs and striking glaciated surroundings.
-
B.
Finsteraarhorn
Finsteraarhorn is a prominent, glaciated peak in the Swiss Alps known for its remote location and striking pyramidal shape.
-
C.
Aletschhorn
Aletschhorn is a prominent high peak in the Swiss Alps known for its extensive glaciation and challenging alpine climbs.
-
D.
Dufourspitze
Dufourspitze is the highest peak of the Monte Rosa massif in the Pennine Alps and the second-highest mountain in the Alps and Western Europe.
-
E.
Schreckhorn
Schreckhorn is a prominent and rugged mountain peak in the Swiss Alps, known for its challenging climbs and striking glaciated scenery.
- F. None of above. chosen
Provenance (5 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ee22081908141868b57596e35 |
completed | March 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad607966748190a5661d47021bf526 |
completed | March 8, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_69ad6124c5f481909427535ec1db38fc |
completed | March 8, 2026, 11:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad61ec8ce081908340301a6f45f5b2 |
completed | March 8, 2026, 11:47 a.m. |
Created at: March 1, 2026, 7:50 p.m.