Triple
T21367624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hirschau |
E526961
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Schwabing |
—
|
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: Schwabing | Statement: [Hirschau, near, Schwabing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwabing Context triple: [Hirschau, near, Schwabing]
-
A.
Schwabing district
chosen
Schwabing district is a vibrant and historic neighborhood in Munich, Germany, known for its bohemian past, lively cultural scene, and proximity to major parks and universities.
-
B.
Giesing
Giesing is a district in Munich, Germany, known as a historically working-class neighborhood that today combines residential areas with notable institutions such as the nearby Stadelheim Prison.
-
C.
Schwanthalerhöhe
Schwanthalerhöhe is a district in Munich, Germany, known for its mix of historic residential areas, cultural venues, and proximity to the Theresienwiese Oktoberfest grounds.
-
D.
Oststadt
Oststadt is a central district of Hanover, Germany, known for its urban residential areas, cultural venues, and proximity to the city’s main commercial and administrative centers.
-
E.
Marienviertel
Marienviertel is a historic quarter in the old town of Berlin, Germany, known for its medieval origins and proximity to key civic buildings.
- 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5bae5eb88190be6d9ff4dc03d52b |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 5:09 p.m.