Triple
T11479429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franz von Sickingen |
E272103
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
Ebernburg
Ebernburg is a historic castle in Rhineland-Palatinate, Germany, known as a stronghold of the early Reformation and the seat of knight Franz von Sickingen.
|
E1006566
|
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: Ebernburg | Statement: [Franz von Sickingen, birthPlace, Ebernburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebernburg Context triple: [Franz von Sickingen, birthPlace, Ebernburg]
-
A.
Ebern
Ebern is a small historic town in northern Bavaria, Germany, known for its medieval architecture and location within the Haßberge region.
-
B.
Burgkunstadt
Burgkunstadt is a small Bavarian town in northern Germany known for its historic center and location in the Upper Franconia region.
-
C.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
D.
Ebersdorf
Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
-
E.
Euerbach
Euerbach is a small municipality in the Schweinfurt district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
- 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: Ebernburg Triple: [Franz von Sickingen, birthPlace, Ebernburg]
Generated description
Ebernburg is a historic castle in Rhineland-Palatinate, Germany, known as a stronghold of the early Reformation and the seat of knight Franz von Sickingen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ebernburg Target entity description: Ebernburg is a historic castle in Rhineland-Palatinate, Germany, known as a stronghold of the early Reformation and the seat of knight Franz von Sickingen.
-
A.
Ebern
Ebern is a small historic town in northern Bavaria, Germany, known for its medieval architecture and location within the Haßberge region.
-
B.
Burgkunstadt
Burgkunstadt is a small Bavarian town in northern Germany known for its historic center and location in the Upper Franconia region.
-
C.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
D.
Ebersdorf
Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
-
E.
Euerbach
Euerbach is a small municipality in the Schweinfurt district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294f0e948190b2e106beb86e4b2c |
completed | April 9, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b76e0cc8190aa7303347e0183d4 |
completed | May 3, 2026, 12:48 a.m. |
| NEDg | Description generation | batch_69f69d48e6948190a13afe3b8943d877 |
completed | May 3, 2026, 12:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69dfa2b8481908827025a28bfb056 |
completed | May 3, 2026, 12:59 a.m. |
Created at: April 8, 2026, 9:36 p.m.