Triple
T23089461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blomberg (Lippe) |
E575703
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Reelkirchen
Reelkirchen is a village and district within the town of Blomberg in the Lippe region of North Rhine-Westphalia, Germany.
|
E1584814
|
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: Reelkirchen | Statement: [Blomberg (Lippe), hasSubdivision, Reelkirchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reelkirchen Context triple: [Blomberg (Lippe), hasSubdivision, Reelkirchen]
-
A.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
B.
Burgkirchen
Burgkirchen is a municipality in southeastern Bavaria, Germany, known for its location in the rural, industrially influenced region near the Austrian border.
-
C.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
-
D.
Kirchlindach
Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
-
E.
Dischingen
Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
- 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: Reelkirchen Triple: [Blomberg (Lippe), hasSubdivision, Reelkirchen]
Generated description
Reelkirchen is a village and district within the town of Blomberg in the Lippe region of North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Reelkirchen Target entity description: Reelkirchen is a village and district within the town of Blomberg in the Lippe region of North Rhine-Westphalia, Germany.
-
A.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
B.
Burgkirchen
Burgkirchen is a municipality in southeastern Bavaria, Germany, known for its location in the rural, industrially influenced region near the Austrian border.
-
C.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
-
D.
Kirchlindach
Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
-
E.
Dischingen
Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
- 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18da8818481908d768a0462f3f837 |
completed | April 29, 2026, 4:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c67729c508190b90b2b7c7d1444f9 |
completed | May 19, 2026, 1:36 p.m. |
| NEDg | Description generation | batch_6a0c72132a608190b44c96de39b7187a |
completed | May 19, 2026, 2:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c76f0f4bc81909912d2196e969cf1 |
completed | May 19, 2026, 2:42 p.m. |
Created at: April 17, 2026, 3:57 p.m.