Triple
T9146459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Münsing |
E219467
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Sankt Heinrich
Sankt Heinrich is a small village in Bavaria, Germany, that forms part of the municipality of Münsing near Lake Starnberg.
|
E781074
|
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: Sankt Heinrich | Statement: [Münsing, hasSubdivision, Sankt Heinrich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sankt Heinrich Context triple: [Münsing, hasSubdivision, Sankt Heinrich]
-
A.
St. Leonhard
St. Leonhard is a locality near Salzburg, Austria, known as the valley station area for the Untersbergbahn cable car that ascends the Untersberg mountain.
-
B.
St. Kajetan
St. Kajetan is the common name for the Theatinerkirche, a prominent Baroque Catholic church in Munich, Germany.
-
C.
Altkönig
Altkönig is a prominent mountain peak in Germany’s Taunus range, known for its scenic hiking trails and remains of ancient Celtic fortifications.
-
D.
Creutzwald
Creutzwald is a small industrial town in northeastern France near the German border, known historically for its coal mining and glassmaking industries.
-
E.
Tannenkirch
Tannenkirch is a village in the Black Forest region of southwestern Germany that forms one of the districts of the town of Kandern in Baden-Württemberg.
- 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: Sankt Heinrich Triple: [Münsing, hasSubdivision, Sankt Heinrich]
Generated description
Sankt Heinrich is a small village in Bavaria, Germany, that forms part of the municipality of Münsing near Lake Starnberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sankt Heinrich Target entity description: Sankt Heinrich is a small village in Bavaria, Germany, that forms part of the municipality of Münsing near Lake Starnberg.
-
A.
St. Leonhard
St. Leonhard is a locality near Salzburg, Austria, known as the valley station area for the Untersbergbahn cable car that ascends the Untersberg mountain.
-
B.
St. Kajetan
St. Kajetan is the common name for the Theatinerkirche, a prominent Baroque Catholic church in Munich, Germany.
-
C.
Altkönig
Altkönig is a prominent mountain peak in Germany’s Taunus range, known for its scenic hiking trails and remains of ancient Celtic fortifications.
-
D.
Creutzwald
Creutzwald is a small industrial town in northeastern France near the German border, known historically for its coal mining and glassmaking industries.
-
E.
Tannenkirch
Tannenkirch is a village in the Black Forest region of southwestern Germany that forms one of the districts of the town of Kandern in Baden-Württemberg.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca917914c8190b97ca9169bbd1e5e |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0482995cc81909bfc202cbab7f8a1 |
completed | April 3, 2026, 11:07 p.m. |
| NEDg | Description generation | batch_69d0496672a881909c1ac91a7ec1a2a1 |
completed | April 3, 2026, 11:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d04a35451881909dfe6795b743b026 |
completed | April 3, 2026, 11:16 p.m. |
Created at: March 30, 2026, 7:20 p.m.