Triple
T1691010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Wallen |
E36547
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Nieuwmarkt area |
E159526
|
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: Nieuwmarkt area | Statement: [De Wallen, contains, Nieuwmarkt area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nieuwmarkt area Context triple: [De Wallen, contains, Nieuwmarkt area]
-
A.
Nieuwmarkt area
chosen
The Nieuwmarkt area is a historic square and surrounding neighborhood in central Amsterdam known for its lively market, cafés, and the iconic Waag building.
-
B.
Jordaan neighborhood
The Jordaan neighborhood is a historic and picturesque district in Amsterdam known for its narrow streets, canals, art galleries, cafés, and vibrant local culture.
-
C.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
-
D.
Binnenstad
Binnenstad is the historic city center of Utrecht in the Netherlands, known for its medieval architecture, canals, and cultural landmarks.
-
E.
Waterlooplein market
Waterlooplein market is a famous daily flea market in central Amsterdam known for its vintage clothes, antiques, and eclectic second-hand goods.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6298fa748190acabb9f1d42bd3f5 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad79947c908190b807205bd44c3254 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.