Triple
T11282446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Wassenberg |
E267096
|
entity |
| Predicate | hasAncestralSeat |
P2536
|
FINISHED |
| Object |
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
|
E915330
|
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: Wassenberg | Statement: [House of Wassenberg, hasAncestralSeat, Wassenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wassenberg Context triple: [House of Wassenberg, hasAncestralSeat, Wassenberg]
-
A.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
B.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
C.
Wildenberg
Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
-
D.
Bassenge
Bassenge is a municipality in the province of Liège in eastern Belgium, known for its rural character and location in the Geer valley near the Dutch border.
-
E.
De Wolden
De Wolden is a rural municipality in the northeastern Netherlands known for its scenic landscapes, small villages, and agricultural character.
- 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: Wassenberg Triple: [House of Wassenberg, hasAncestralSeat, Wassenberg]
Generated description
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wassenberg Target entity description: Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
A.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
B.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
C.
Wildenberg
Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
-
D.
Bassenge
Bassenge is a municipality in the province of Liège in eastern Belgium, known for its rural character and location in the Geer valley near the Dutch border.
-
E.
De Wolden
De Wolden is a rural municipality in the northeastern Netherlands known for its scenic landscapes, small villages, and agricultural character.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e96e15708190b3a1cccfbbe65882 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f471490081909036362c58e1e727 |
completed | April 19, 2026, 3:27 p.m. |
| NEDg | Description generation | batch_69e4f95be4b08190bebb2078406cb7ba |
completed | April 19, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4ff6b7d248190b4dd885280e09a8e |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 8, 2026, 9:31 p.m.