Triple
T23452946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weinheim |
E567834
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Marktplatz
Marktplatz is the historic central market square of Weinheim, known for its picturesque old-town atmosphere and traditional events.
|
E1586673
|
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: Marktplatz | Statement: [Weinheim, hasLandmark, Marktplatz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marktplatz Context triple: [Weinheim, hasLandmark, Marktplatz]
-
A.
Marktplatz
Marktplatz was the historical central marketplace of Munich, later renamed Marienplatz, which has long served as the city’s main public square and social hub.
-
B.
Marktplatz
Marktplatz is the central historic market square of Schwäbisch Gmünd, known for its traditional architecture and role as a focal point of civic life and events.
-
C.
Marktplatz
Marktplatz is the central historic market square in Heidelberg, Germany, known for its surrounding baroque buildings, cafés, and proximity to the Church of the Holy Spirit.
-
D.
Marktplatz
Marktplatz is the central market square of Karlsruhe, Germany, serving as a key civic and commercial hub of the city.
-
E.
Markt
Markt is the central market square of Bruges, Belgium, known for its historic guild houses, bustling cafes, and prominent Belfry tower.
- 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: Marktplatz Triple: [Weinheim, hasLandmark, Marktplatz]
Generated description
Marktplatz is the historic central market square of Weinheim, known for its picturesque old-town atmosphere and traditional events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marktplatz Target entity description: Marktplatz is the historic central market square of Weinheim, known for its picturesque old-town atmosphere and traditional events.
-
A.
Marktplatz
Marktplatz was the historical central marketplace of Munich, later renamed Marienplatz, which has long served as the city’s main public square and social hub.
-
B.
Marktplatz
Marktplatz is the central historic market square of Schwäbisch Gmünd, known for its traditional architecture and role as a focal point of civic life and events.
-
C.
Marktplatz
Marktplatz is the central historic market square in Heidelberg, Germany, known for its surrounding baroque buildings, cafés, and proximity to the Church of the Holy Spirit.
-
D.
Marktplatz
Marktplatz is the central market square of Karlsruhe, Germany, serving as a key civic and commercial hub of the city.
-
E.
Markt
Markt is the central market square of Bruges, Belgium, known for its historic guild houses, bustling cafes, and prominent Belfry tower.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a694f19081909117bc9b10ca8a83 |
completed | April 29, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c67c0c2d081909da467271800b69d |
completed | May 19, 2026, 1:38 p.m. |
| NEDg | Description generation | batch_6a0c7218a358819082d8b19b57b61013 |
completed | May 19, 2026, 2:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c76ed37b08190af81b4ae2dc7c028 |
completed | May 19, 2026, 2:42 p.m. |
Created at: April 17, 2026, 5:52 p.m.