Triple
T13380395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlsplatz |
E319301
|
entity |
| Predicate | crossedBy |
P416
|
FINISHED |
| Object |
Operngasse
Operngasse is a street in central Vienna, Austria, running near major landmarks such as the Vienna State Opera and Karlsplatz.
|
E1041355
|
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: Operngasse | Statement: [Karlsplatz, crossedBy, Operngasse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Operngasse Context triple: [Karlsplatz, crossedBy, Operngasse]
-
A.
Schauplatzgasse
Schauplatzgasse is a street in the historic center of Bern, Switzerland, located near the Federal Palace and the Bundesplatz.
-
B.
Marktgasse
Marktgasse is a central historic street in Bern, Switzerland, known for its arcaded buildings, shops, and proximity to landmarks such as the Käfigturm.
-
C.
Saalgasse
Saalgasse is a historic street in Frankfurt’s old town, notable for its postwar modernist townhouses built on medieval foundations.
-
D.
Ernsgaden
Ernsgaden is a small Bavarian municipality located in the district of Pfaffenhofen an der Ilm in southern Germany.
-
E.
Gerichtstraße
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
- 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: Operngasse Triple: [Karlsplatz, crossedBy, Operngasse]
Generated description
Operngasse is a street in central Vienna, Austria, running near major landmarks such as the Vienna State Opera and Karlsplatz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Operngasse Target entity description: Operngasse is a street in central Vienna, Austria, running near major landmarks such as the Vienna State Opera and Karlsplatz.
-
A.
Schauplatzgasse
Schauplatzgasse is a street in the historic center of Bern, Switzerland, located near the Federal Palace and the Bundesplatz.
-
B.
Marktgasse
Marktgasse is a central historic street in Bern, Switzerland, known for its arcaded buildings, shops, and proximity to landmarks such as the Käfigturm.
-
C.
Saalgasse
Saalgasse is a historic street in Frankfurt’s old town, notable for its postwar modernist townhouses built on medieval foundations.
-
D.
Ernsgaden
Ernsgaden is a small Bavarian municipality located in the district of Pfaffenhofen an der Ilm in southern Germany.
-
E.
Gerichtstraße
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce694788190881d1feac5b75720 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7397f098c8190a2062d8c1a74d28f |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b181b80819095b7963bdb366326 |
completed | May 3, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73c1d46008190a9fe3ffe1ac76bca |
completed | May 3, 2026, 12:14 p.m. |
Created at: April 9, 2026, 9:33 p.m.