Triple
T20497845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwabing |
E502919
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Altschwabing
Altschwabing is a historic and culturally rich quarter of Munich known for its traditional architecture, bohemian past, and vibrant urban life.
|
E1435593
|
NE FINISHED |
How this triple was built (4 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: Altschwabing | Statement: [Schwabing, hasPart, Altschwabing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altschwabing Context triple: [Schwabing, hasPart, Altschwabing]
-
A.
Wittighausen
Wittighausen is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Königswartha
Königswartha is a small municipality in the Upper Lusatia region of Saxony in eastern Germany.
-
D.
Weinböhla
Weinböhla is a small municipality in the German state of Saxony, known for its wine-growing tradition and location near the Elbe River between Dresden and Meißen.
-
E.
Wolpertshausen
Wolpertshausen is a small rural municipality in the German state of Baden-Württemberg, known for its agricultural character and location within the Hohenlohe region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Altschwabing Triple: [Schwabing, hasPart, Altschwabing]
Generated description
Altschwabing is a historic and culturally rich quarter of Munich known for its traditional architecture, bohemian past, and vibrant urban life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Altschwabing Target entity description: Altschwabing is a historic and culturally rich quarter of Munich known for its traditional architecture, bohemian past, and vibrant urban life.
-
A.
Wittighausen
Wittighausen is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Königswartha
Königswartha is a small municipality in the Upper Lusatia region of Saxony in eastern Germany.
-
D.
Weinböhla
Weinböhla is a small municipality in the German state of Saxony, known for its wine-growing tradition and location near the Elbe River between Dresden and Meißen.
-
E.
Wolpertshausen
Wolpertshausen is a small rural municipality in the German state of Baden-Württemberg, known for its agricultural character and location within the Hohenlohe region.
- F. None of above. chosen
Provenance (5 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbefe4c819098af5bfd4d92341d |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a089d31f68881908b7676ca5561a76f |
completed | May 16, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a089db22fcc819094d595a3ce4e19a6 |
completed | May 16, 2026, 4:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a089e4c21d88190a6c1ddf8e0879cb1 |
completed | May 16, 2026, 4:41 p.m. |
Created at: April 16, 2026, 11:35 a.m.