Triple
T13601820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Tell |
E324961
|
entity |
| Predicate | placeOfOrigin |
P3743
|
FINISHED |
| Object | Bürglen |
E705854
|
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: Bürglen | Statement: [William Tell, placeOfOrigin, Bürglen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bürglen Context triple: [William Tell, placeOfOrigin, Bürglen]
-
A.
Bürglen
chosen
Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
-
B.
Ennetbürgen
Ennetbürgen is a Swiss lakeside municipality known for its scenic location on Lake Lucerne and proximity to Mount Bürgenstock in central Switzerland.
-
C.
Besseggen
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
-
D.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
E.
Bürmoos
Bürmoos is a small Austrian municipality located in the state of Salzburg, known for its residential character and proximity to the city of Salzburg.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07ad3f48190a2173e42c5cfedb1 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce60b1248190addfbfc1c5ccd2d1 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 9:49 p.m.