Triple
T16510995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgdorf |
E401058
|
entity |
| Predicate | hasRailConnectionTo |
P848
|
FINISHED |
| Object | Thun |
E113677
|
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: Thun | Statement: [Burgdorf, hasRailConnectionTo, Thun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thun Context triple: [Burgdorf, hasRailConnectionTo, Thun]
-
A.
Thun
chosen
Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
-
B.
Brienz
Brienz is a picturesque Swiss village in the Bernese Oberland, known for its lakeside setting on Lake Brienz and its traditional woodcarving craftsmanship.
-
C.
Sihlwald
Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
-
D.
Saanen
Saanen is a picturesque Swiss village in the Bernese Oberland known for its traditional chalets, alpine scenery, and proximity to the upscale resort town of Gstaad.
-
E.
Kiental
Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e55fe7c8190abc957bdd326d1bc |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091872e648190b805aa4e41bcbb6d |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:14 a.m.