Triple
T15480329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 motorway |
E376897
|
entity |
| Predicate | runsThroughCity |
P10456
|
FINISHED |
| Object | Weimar |
E111310
|
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: Weimar | Statement: [A4 motorway, runsThroughCity, Weimar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weimar Context triple: [A4 motorway, runsThroughCity, Weimar]
-
A.
Weimar
chosen
Weimar is a historic German city renowned as a center of culture and the arts, associated with figures like Goethe and Schiller and pivotal movements in modern design and architecture.
-
B.
Weimar (Lahn)
Weimar (Lahn) is a small municipality in the German state of Hesse, located near the university city of Marburg.
-
C.
Nuremberg
Nuremberg is a historic city in Bavaria, Germany, known for its medieval architecture and its role as the site of the post–World War II war crimes tribunals.
-
D.
Gotha
Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
-
E.
Wiesbaden
Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8a77a081909f12f13660452f4a |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d4661088190bb53161247effcc4 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:34 a.m.