Triple
T20225849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flacht (Weissach) |
E495375
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Weissach |
—
|
NE NERFINISHED |
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: Weissach | Statement: [Flacht (Weissach), partOf, Weissach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weissach Context triple: [Flacht (Weissach), partOf, Weissach]
-
A.
Weissach
chosen
Weissach is a municipality in the German state of Baden-Württemberg, known especially for hosting Porsche’s main research and development center and test track.
-
B.
Maroldsweisach
Maroldsweisach is a municipality in the Haßberge district of northern Bavaria, Germany, known for its rural setting and historic Franconian character.
-
C.
Vaihingen
Vaihingen is a district in the southwest of Stuttgart, Germany, known for its mix of residential areas, business parks, and proximity to major transport links.
-
D.
Pfronten
Pfronten is a Bavarian municipality in southern Germany known for its scenic Alpine setting near the Austrian border and outdoor recreation opportunities.
-
E.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd9c1f4819092a98f5fa84fb795 |
completed | April 20, 2026, 6:26 p.m. |
Created at: April 11, 2026, 11:39 p.m.