Triple
T14887684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villingen-Schwenningen |
E359670
|
entity |
| Predicate | hasCityPart |
P12399
|
FINISHED |
| Object | Villingen |
E1145986
|
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: Villingen | Statement: [Villingen-Schwenningen, hasCityPart, Villingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villingen Context triple: [Villingen-Schwenningen, hasCityPart, Villingen]
-
A.
Villingen
chosen
Villingen is a historic German town in the Black Forest region, now part of the twin city of Villingen-Schwenningen in the state of Baden-Württemberg.
-
B.
Dischingen
Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
-
C.
Klemzig
Klemzig is a suburb of Adelaide, South Australia, known as one of the city's earliest German settlements and now a primarily residential area.
-
D.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
-
E.
Vaterstetten
Vaterstetten is a municipality in the district of Ebersberg near Munich in Bavaria, Germany, known as a residential suburb with strong transport links to the Bavarian capital.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec12de8819097cd83530e54f54b |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 2:08 a.m.