Triple
T22939718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibbenbüren |
E569686
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Schierloh
Schierloh is a district or neighborhood within the town of Ibbenbüren in North Rhine-Westphalia, Germany.
|
E1579196
|
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: Schierloh | Statement: [Ibbenbüren, hasSubdivision, Schierloh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schierloh Context triple: [Ibbenbüren, hasSubdivision, Schierloh]
-
A.
Lohne
Lohne is a town in Lower Saxony, Germany, known for its industrial economy and location within the Vechta district.
-
B.
Niederschlema
Niederschlema is a historic spa and former mining town in Saxony, Germany, known for its role in the Ore Mountain mining region and its radon-rich therapeutic springs.
-
C.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
D.
Albersloh
Albersloh is a village in North Rhine-Westphalia, Germany, known for its rural character and location along the Werse River.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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: Schierloh Triple: [Ibbenbüren, hasSubdivision, Schierloh]
Generated description
Schierloh is a district or neighborhood within the town of Ibbenbüren in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schierloh Target entity description: Schierloh is a district or neighborhood within the town of Ibbenbüren in North Rhine-Westphalia, Germany.
-
A.
Lohne
Lohne is a town in Lower Saxony, Germany, known for its industrial economy and location within the Vechta district.
-
B.
Niederschlema
Niederschlema is a historic spa and former mining town in Saxony, Germany, known for its role in the Ore Mountain mining region and its radon-rich therapeutic springs.
-
C.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
D.
Albersloh
Albersloh is a village in North Rhine-Westphalia, Germany, known for its rural character and location along the Werse River.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813844b88190b05d3829b0c423c4 |
completed | April 29, 2026, 3:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c4c6417ec8190b4bcf39b5bb3f9e6 |
completed | May 19, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_6a0c4e0220308190bbab2c2d1a2dac1e |
completed | May 19, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c4e80b314819085639a0f6c22872d |
completed | May 19, 2026, 11:50 a.m. |
Created at: April 17, 2026, 3:45 p.m.