Triple
T4571645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freiberg |
E123043
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Obermarkt
Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
|
E454206
|
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: Obermarkt | Statement: [Freiberg, hasLandmark, Obermarkt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Obermarkt Context triple: [Freiberg, hasLandmark, Obermarkt]
-
A.
Obermarkt
Obermarkt is a historic central market square in the city of Görlitz, Germany, known for its well-preserved architecture and role as a focal point of urban life.
-
B.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
C.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
-
D.
Oberaudorf
Oberaudorf is a small Bavarian town in southern Germany near the Austrian border, known for its alpine scenery and ski tourism.
-
E.
Marchfeld
Marchfeld is a fertile lowland region in eastern Austria known for its intensive agriculture and vegetable production.
- 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: Obermarkt Triple: [Freiberg, hasLandmark, Obermarkt]
Generated description
Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Obermarkt Target entity description: Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
-
A.
Obermarkt
Obermarkt is a historic central market square in the city of Görlitz, Germany, known for its well-preserved architecture and role as a focal point of urban life.
-
B.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
C.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
-
D.
Oberaudorf
Oberaudorf is a small Bavarian town in southern Germany near the Austrian border, known for its alpine scenery and ski tourism.
-
E.
Marchfeld
Marchfeld is a fertile lowland region in eastern Austria known for its intensive agriculture and vegetable production.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c5afa48190bb8505e2cc16e89f |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3cf5e10819099b2927c6f571673 |
completed | March 20, 2026, 11:10 p.m. |
| NEDg | Description generation | batch_69bdd7f1efd0819089410e63f853175b |
completed | March 20, 2026, 11:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdd86be2c48190af8011a983f26b0d |
completed | March 20, 2026, 11:29 p.m. |
Created at: March 20, 2026, 1:10 p.m.