Triple
T4945630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baarn railway station |
E111041
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Baarn town centre |
E111040
|
NE FINISHED |
How this triple was built (2 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 town centre | Statement: [Baarn railway station, locatedNear, Baarn town centre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baarn town centre Context triple: [Baarn railway station, locatedNear, Baarn town centre]
-
A.
Baarn
chosen
Baarn is a town and municipality in the Dutch province of Utrecht, known for its historic royal connections and green, affluent residential character.
-
B.
Ballstad
Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
-
C.
Valbo Köpcentrum
Valbo Köpcentrum is a major regional shopping mall in Valbo, Sweden, featuring a wide range of retail stores, services, and dining options.
-
D.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
E.
Bockum
Bockum is a residential district of the German city of Krefeld, known for its green spaces and affluent neighborhoods.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70aa890c81908e685ec5e88cae1f |
completed | March 20, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81cc862081908b42686f04915238 |
completed | March 21, 2026, 11:32 a.m. |
Created at: March 20, 2026, 1:31 p.m.