Triple
T18102787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thiersch |
E433268
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Kirchscheidungen
Kirchscheidungen is a small village in the German state of Saxony-Anhalt, known as the birthplace of the 19th-century architect and art historian Friedrich von Thiersch.
|
E1304697
|
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: Kirchscheidungen | Statement: [Thiersch, placeOfBirth, Kirchscheidungen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirchscheidungen Context triple: [Thiersch, placeOfBirth, Kirchscheidungen]
-
A.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
B.
Steinwiesen
Steinwiesen is a small municipality in northern Bavaria, Germany, known for its location in the Franconian Forest and its traditional rural character.
-
C.
Spiegelrei
Spiegelrei is a picturesque historic canal quay in Bruges, Belgium, known for its medieval architecture and scenic waterfront views.
-
D.
Kreuzboden
Kreuzboden is a popular alpine recreation area in the Swiss Alps above Saas-Grund, known for its scenic mountain views, hiking trails, and ski facilities.
-
E.
Tuchlauben
Tuchlauben is a historic street in Vienna’s city center, known for its upscale shops and proximity to major landmarks in the old town.
- 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: Kirchscheidungen Triple: [Thiersch, placeOfBirth, Kirchscheidungen]
Generated description
Kirchscheidungen is a small village in the German state of Saxony-Anhalt, known as the birthplace of the 19th-century architect and art historian Friedrich von Thiersch.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kirchscheidungen Target entity description: Kirchscheidungen is a small village in the German state of Saxony-Anhalt, known as the birthplace of the 19th-century architect and art historian Friedrich von Thiersch.
-
A.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
B.
Steinwiesen
Steinwiesen is a small municipality in northern Bavaria, Germany, known for its location in the Franconian Forest and its traditional rural character.
-
C.
Spiegelrei
Spiegelrei is a picturesque historic canal quay in Bruges, Belgium, known for its medieval architecture and scenic waterfront views.
-
D.
Kreuzboden
Kreuzboden is a popular alpine recreation area in the Swiss Alps above Saas-Grund, known for its scenic mountain views, hiking trails, and ski facilities.
-
E.
Tuchlauben
Tuchlauben is a historic street in Vienna’s city center, known for its upscale shops and proximity to major landmarks in the old town.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb7be948190b4ed4586f731d6f2 |
completed | April 19, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a035da76a448190909d04d8ecff3a33 |
completed | May 12, 2026, 5:04 p.m. |
| NEDg | Description generation | batch_6a035f5802988190b4ba3b6fd3790d92 |
completed | May 12, 2026, 5:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a035fbf73f88190b4f648d7805db686 |
completed | May 12, 2026, 5:13 p.m. |
Created at: April 10, 2026, 10:28 a.m.