Triple
T5516327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schoenfeld |
E144691
|
entity |
| Predicate | hasAlternativeForm |
P455
|
FINISHED |
| Object |
Schönfeld
Schönfeld is a German surname and place name found in various regions of German-speaking Europe.
|
E529599
|
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: Schönfeld | Statement: [Schoenfeld, hasAlternativeForm, Schönfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schönfeld Context triple: [Schoenfeld, hasAlternativeForm, Schönfeld]
-
A.
Schönried
Schönried is a Swiss alpine village and ski resort in the Bernese Oberland, known for its scenic mountain setting and proximity to the upscale resort area of Gstaad.
-
B.
Geisenfeld
Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
-
C.
Schöneberg
Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
-
D.
Bromberg
Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
-
E.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
- 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: Schönfeld Triple: [Schoenfeld, hasAlternativeForm, Schönfeld]
Generated description
Schönfeld is a German surname and place name found in various regions of German-speaking Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schönfeld Target entity description: Schönfeld is a German surname and place name found in various regions of German-speaking Europe.
-
A.
Schönried
Schönried is a Swiss alpine village and ski resort in the Bernese Oberland, known for its scenic mountain setting and proximity to the upscale resort area of Gstaad.
-
B.
Geisenfeld
Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
-
C.
Schöneberg
Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
-
D.
Bromberg
Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
-
E.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
- 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f5e8ce08190b7f5f2131bebcd4f |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027dd848481908052007e89c3f634 |
completed | March 22, 2026, 5:33 p.m. |
| NEDg | Description generation | batch_69c03847b3348190be97b7c5795df368 |
completed | March 22, 2026, 6:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c038e148a0819080a306307e60d437 |
completed | March 22, 2026, 6:45 p.m. |
Created at: March 22, 2026, 3:33 p.m.