Triple
T1532182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museumplein |
E32467
|
entity |
| Predicate | hasDutchName |
P744
|
FINISHED |
| Object | Museumplein |
E32467
|
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: Museumplein | Statement: [Museumplein, hasDutchName, Museumplein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Museumplein Context triple: [Museumplein, hasDutchName, Museumplein]
-
A.
Museumplein
chosen
Museumplein is a major public square and cultural hub in Amsterdam, known for housing several of the city's most important museums and hosting large events.
-
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.
Weesperplein
Weesperplein is an underground metro station in central Amsterdam that serves as a key stop on multiple Amsterdam Metro lines.
-
D.
Luxemburgplein
Luxemburgplein is a prominent square in Brussels, Belgium, located near the European Parliament and known as a hub for political and social gatherings.
-
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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90816b5e88190aa92a8558e35744b |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb90e16081908d70df182b7efb8a |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:26 p.m.