Triple
T944217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soestdijk Palace |
E20375
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Baarn
Baarn is a town and municipality in the Dutch province of Utrecht, known for its historic royal connections and green, affluent residential character.
|
E111040
|
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: Baarn | Statement: [Soestdijk Palace, locatedIn, Baarn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baarn Context triple: [Soestdijk Palace, locatedIn, Baarn]
-
A.
Werl
Werl is a town in North Rhine-Westphalia, Germany, known for its historical significance and regional correctional facility.
-
B.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
C.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Ahaus
Ahaus is a town in the district of Borken in North Rhine-Westphalia, western Germany, known for its historic castle and role as a regional administrative and cultural center.
- 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: Baarn Triple: [Soestdijk Palace, locatedIn, Baarn]
Generated description
Baarn is a town and municipality in the Dutch province of Utrecht, known for its historic royal connections and green, affluent residential character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baarn Target entity description: Baarn is a town and municipality in the Dutch province of Utrecht, known for its historic royal connections and green, affluent residential character.
-
A.
Werl
Werl is a town in North Rhine-Westphalia, Germany, known for its historical significance and regional correctional facility.
-
B.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
C.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Ahaus
Ahaus is a town in the district of Borken in North Rhine-Westphalia, western Germany, known for its historic castle and role as a regional administrative and cultural center.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a3ed3881908386af140477c514 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826e585208190bf477bf78d162e84 |
completed | March 4, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69a83365d590819085d8e92c1a69aa10 |
completed | March 4, 2026, 1:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a834268c388190ac725f48be8f8ea6 |
completed | March 4, 2026, 1:31 p.m. |
Created at: March 1, 2026, 7:40 p.m.