Triple
T583540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Rosa |
E15107
|
entity |
| Predicate | hasPeak |
P8205
|
FINISHED |
| Object | Parrotspitze |
E72901
|
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: Parrotspitze | Statement: [Monte Rosa, hasPeak, Parrotspitze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parrotspitze Context triple: [Monte Rosa, hasPeak, Parrotspitze]
-
A.
Zugspitze
Zugspitze is the highest mountain in Germany, located in the Bavarian Alps near the Austrian border.
-
B.
Zumsteinspitze
chosen
Zumsteinspitze is one of the high summits of the Monte Rosa massif in the Pennine Alps on the border between Switzerland and Italy.
-
C.
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.
-
D.
Grossglockner
Grossglockner is the tallest mountain in Austria and a prominent peak of the Hohe Tauern range in the Central Eastern Alps.
-
E.
Monte Rosa
Monte Rosa is a prominent massif in the Pennine Alps on the border between Switzerland and Italy, known for being the second-highest mountain in the Alps and Western Europe.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b8745c88190af9672e5fe8396c3 |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a51f33e59c8190b3593b8460411fba |
completed | March 2, 2026, 5:25 a.m. |
Created at: March 1, 2026, 7:33 p.m.