Triple
T1209064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spui |
E25956
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Koningsplein |
E129993
|
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: Koningsplein | Statement: [Spui, locatedNear, Koningsplein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koningsplein Context triple: [Spui, locatedNear, Koningsplein]
-
A.
Koningsplein
chosen
Koningsplein is a central square in Amsterdam known for its proximity to major canals, shopping streets, and the historic city center.
-
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.
Paleisstraat
Paleisstraat is a central street in Amsterdam that runs alongside the Royal Palace and links Dam Square with the Jordaan area.
-
D.
Museumplein
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.
-
E.
Kalverstraat
Kalverstraat is one of Amsterdam’s busiest and most famous shopping streets, known for its dense concentration of retail stores and central location.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde30ce08190ab60a181ad2d321d |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad36f6d9288190ad64dc1bc9e9f8c1 |
completed | March 8, 2026, 8:44 a.m. |
Created at: March 1, 2026, 7:46 p.m.