Triple
T8877830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wibautstraat |
E211332
|
entity |
| Predicate | locatedOnStreet |
P959
|
FINISHED |
| Object | Wibautstraat |
E211332
|
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: Wibautstraat | Statement: [Wibautstraat, locatedOnStreet, Wibautstraat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wibautstraat Context triple: [Wibautstraat, locatedOnStreet, Wibautstraat]
-
A.
Wibautstraat
chosen
Wibautstraat is a metro station in Amsterdam that serves as a stop on the city’s rapid transit network.
-
B.
De Lairessestraat
De Lairessestraat is a prominent street in Amsterdam’s Oud-Zuid district, known for its upscale residential buildings and proximity to cultural attractions.
-
C.
Van Baerlestraat
Van Baerlestraat is a major street in Amsterdam known for running alongside the Museumplein and providing access to several prominent museums and cultural institutions.
-
D.
Kalverstraat
Kalverstraat is one of Amsterdam’s busiest and most famous shopping streets, known for its dense concentration of retail stores and central location.
-
E.
Valkenburgerstraat
Valkenburgerstraat is a street in central Amsterdam, Netherlands, located near the Waterlooplein area and served by the city’s metro network.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61496870819097c55c73aca62aac |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd78f35881909c15249b58a1ce03 |
completed | April 3, 2026, 5:48 p.m. |
Created at: March 30, 2026, 6:52 p.m.