Triple
T12045395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roßlau (Elbe) |
E286772
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
St. Marien church
St. Marien church is a historic Christian church and notable architectural landmark located in Roßlau (Elbe), Germany.
|
E961913
|
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: St. Marien church | Statement: [Roßlau (Elbe), hasLandmark, St. Marien church]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Marien church Context triple: [Roßlau (Elbe), hasLandmark, St. Marien church]
-
A.
St. Marien church
St. Marien church is a historic Christian church and prominent architectural landmark located in the town of Marienberg, Germany.
-
B.
St. Marien Church
St. Marien Church is a historic Lutheran church and prominent architectural landmark in the city of Flensburg, Germany.
-
C.
St. Marien Church
St. Marien Church is a historic Christian church in Freyburg (Unstrut), Germany, noted for its medieval architecture and cultural significance in the region.
-
D.
St. Marien Church
St. Marien Church is a historic Christian church and notable architectural landmark located in the town of Lünen, Germany.
-
E.
Christuskirche
Christuskirche is a historic Lutheran church in Windhoek, Namibia, renowned for its distinctive German colonial architecture and status as a city landmark.
- 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: St. Marien church Triple: [Roßlau (Elbe), hasLandmark, St. Marien church]
Generated description
St. Marien church is a historic Christian church and notable architectural landmark located in Roßlau (Elbe), Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: St. Marien church Target entity description: St. Marien church is a historic Christian church and notable architectural landmark located in Roßlau (Elbe), Germany.
-
A.
St. Marien church
St. Marien church is a historic Christian church and prominent architectural landmark located in the town of Marienberg, Germany.
-
B.
St. Marien Church
St. Marien Church is a historic Lutheran church and prominent architectural landmark in the city of Flensburg, Germany.
-
C.
St. Marien Church
St. Marien Church is a historic Christian church in Freyburg (Unstrut), Germany, noted for its medieval architecture and cultural significance in the region.
-
D.
St. Marien Church
St. Marien Church is a historic Christian church and notable architectural landmark located in the town of Lünen, Germany.
-
E.
Christuskirche
Christuskirche is a historic Lutheran church in Windhoek, Namibia, renowned for its distinctive German colonial architecture and status as a city landmark.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49db574bc8190a0f2f858a2ff788d |
completed | May 1, 2026, 12:33 p.m. |
| NEDg | Description generation | batch_69f53d9460bc8190869f2b7d095d98cb |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564d2b4348190abf2d09ae00aea37 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.