Triple
T9870771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Karlshafen |
E239949
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Helmarshausen
Helmarshausen is a historic district of the spa town Bad Karlshafen in northern Hesse, Germany, known for its medieval heritage and former Benedictine monastery.
|
E911080
|
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: Helmarshausen | Statement: [Bad Karlshafen, hasSubdivision, Helmarshausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helmarshausen Context triple: [Bad Karlshafen, hasSubdivision, Helmarshausen]
-
A.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Weipertshausen
Weipertshausen is a small locality that forms part of the municipality of Münsing in Bavaria, Germany.
-
C.
Merzhausen
Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Waigolshausen
Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian 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: Helmarshausen Triple: [Bad Karlshafen, hasSubdivision, Helmarshausen]
Generated description
Helmarshausen is a historic district of the spa town Bad Karlshafen in northern Hesse, Germany, known for its medieval heritage and former Benedictine monastery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helmarshausen Target entity description: Helmarshausen is a historic district of the spa town Bad Karlshafen in northern Hesse, Germany, known for its medieval heritage and former Benedictine monastery.
-
A.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Weipertshausen
Weipertshausen is a small locality that forms part of the municipality of Münsing in Bavaria, Germany.
-
C.
Merzhausen
Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Waigolshausen
Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d62628819094786a49b9bcd09b |
completed | April 2, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4963545f481909ecc360480b1fc37 |
completed | April 19, 2026, 8:45 a.m. |
| NEDg | Description generation | batch_69e49a97db808190aa22d6a103a13e58 |
completed | April 19, 2026, 9:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e49d71e81c8190af73931ed30e04be |
completed | April 19, 2026, 9:16 a.m. |
Created at: March 30, 2026, 8:36 p.m.