Triple
T8704450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appelstraße campus |
E206611
|
entity |
| Predicate | street |
P959
|
FINISHED |
| Object |
Appelstraße
Appelstraße is a street in Hanover, Germany, known for hosting parts of the Leibniz University of Hanover’s campus and various academic facilities.
|
E751461
|
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: Appelstraße | Statement: [Appelstraße campus, street, Appelstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Appelstraße Context triple: [Appelstraße campus, street, Appelstraße]
-
A.
Otisstraße
Otisstraße is a Berlin U-Bahn station on line U6 located in the Reinickendorf district of the city.
-
B.
Brienner Straße
Brienner Straße is a historic boulevard in Munich, Germany, known for its neoclassical architecture and its role as one of the city’s grand royal avenues.
-
C.
Grunerstraße
Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
-
D.
Eichhornstraße
Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
-
E.
Beusselstraße
Beusselstraße is a railway station in Berlin that serves the city's circular Ringbahn line and connects the surrounding Moabit area to the wider S-Bahn network.
- 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: Appelstraße Triple: [Appelstraße campus, street, Appelstraße]
Generated description
Appelstraße is a street in Hanover, Germany, known for hosting parts of the Leibniz University of Hanover’s campus and various academic facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Appelstraße Target entity description: Appelstraße is a street in Hanover, Germany, known for hosting parts of the Leibniz University of Hanover’s campus and various academic facilities.
-
A.
Otisstraße
Otisstraße is a Berlin U-Bahn station on line U6 located in the Reinickendorf district of the city.
-
B.
Brienner Straße
Brienner Straße is a historic boulevard in Munich, Germany, known for its neoclassical architecture and its role as one of the city’s grand royal avenues.
-
C.
Grunerstraße
Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
-
D.
Eichhornstraße
Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
-
E.
Beusselstraße
Beusselstraße is a railway station in Berlin that serves the city's circular Ringbahn line and connects the surrounding Moabit area to the wider S-Bahn network.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fb43f081909df5d1e31cb1ec04 |
completed | March 31, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef41e3ec08190b29adf483cdf8cc3 |
completed | April 2, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69cef68b33948190a259870e320da5e5 |
completed | April 2, 2026, 11:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef6fb42e48190b09d49d3a2fee4ae |
completed | April 2, 2026, 11:08 p.m. |
Created at: March 30, 2026, 6:34 p.m.