Triple
T470356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stedelijk Museum |
E8541
|
entity |
| Predicate | locatedIn |
P40
|
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: [Stedelijk Museum, locatedIn, Museumplein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Museumplein Context triple: [Stedelijk Museum, locatedIn, 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.
Muntplein
Muntplein is a central square in Amsterdam, known as a busy traffic hub near the historic city center and the Munttoren (Mint Tower).
-
D.
Prinsengracht
Prinsengracht is one of Amsterdam’s main historic canals, known for its picturesque waterways, houseboats, and traditional canal houses.
-
E.
Utrechtsestraat
Utrechtsestraat is a well-known shopping and dining street in central Amsterdam, noted for its historic canalside setting and mix of boutiques, 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efef8b788190857ebf66df562d59 |
completed | Feb. 28, 2026, 1:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a49eb7b49c819098352f36d020cde7 |
completed | March 1, 2026, 8:16 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.