Triple
T10149008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Begijnhof |
E232581
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Spui square |
E593895
|
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: Spui square | Statement: [Begijnhof, near, Spui square]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spui square Context triple: [Begijnhof, near, Spui square]
-
A.
Spui square
chosen
Spui square is a central public square in Amsterdam known for its book markets, cultural venues, and proximity to historic sites like the Begijnhof.
-
B.
Vredenburg square
Vredenburg square is a central public square in the Dutch city of Utrecht, known as a major hub for shopping, events, and public transport.
-
C.
Vrijthof square
Vrijthof square is the central and most famous square in Maastricht, known for its historic churches, lively cafés, and frequent cultural events and festivals.
-
D.
Wapper square
Wapper square is a historic public square in the center of Antwerp, Belgium, known for landmarks such as the Rubenshuis museum.
-
E.
Leidseplein
Leidseplein is a lively square in central Amsterdam known for its theaters, nightlife, street performers, and numerous cafés and restaurants.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec024da481908b8170fcf3b18e67 |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e6369c848190984394eedf2f07eb |
completed | April 5, 2026, 10:46 p.m. |
Created at: March 30, 2026, 9:08 p.m.