Triple
T12655126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merwedeplein 37, Amsterdam |
E302259
|
entity |
| Predicate | hasNearbyPublicSpace |
P3449
|
FINISHED |
| Object | Merwedeplein |
E1009032
|
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: Merwedeplein | Statement: [Merwedeplein 37, Amsterdam, hasNearbyPublicSpace, Merwedeplein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merwedeplein Context triple: [Merwedeplein 37, Amsterdam, hasNearbyPublicSpace, Merwedeplein]
-
A.
Merwedeplein
chosen
Merwedeplein is a residential square in Amsterdam best known for being the neighborhood where Anne Frank lived before going into hiding.
-
B.
Paleizenplein
Paleizenplein is the prominent public square in central Brussels that fronts the Royal Palace and serves as a key ceremonial and urban landmark in the Belgian capital.
-
C.
Natieplein
Natieplein is the Dutch name for Place de la Nation, a notable public square in Paris, France.
-
D.
Weesperplein
Weesperplein is an underground metro station in central Amsterdam that serves as a key stop on multiple Amsterdam Metro lines.
-
E.
Gelderlandplein
Gelderlandplein is a major shopping center in Amsterdam’s Buitenveldert district, featuring a wide range of retail stores, restaurants, and services.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961620b188190a8a8569f1133a9cf |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af45ea888190a4b2d0c1730a06ef |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:18 p.m.