Triple
T1691020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Wallen |
E36547
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Nieuwmarkt |
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 | Statement: [De Wallen, locatedNear, Nieuwmarkt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nieuwmarkt Context triple: [De Wallen, locatedNear, Nieuwmarkt]
-
A.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
B.
Nieuwkoop
Nieuwkoop is a rural municipality and town in South Holland, Netherlands, known for its lakes, peatlands, and nature reserves.
-
C.
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.
-
D.
Binnenstad
Binnenstad is the historic city center of Utrecht in the Netherlands, known for its medieval architecture, canals, and cultural landmarks.
-
E.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
- 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.