Triple
T7916569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Square |
E183841
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object |
Hobbemastraat
Hobbemastraat is a street in Amsterdam, Netherlands, known for its proximity to major museums and cultural attractions near Museumplein.
|
E712084
|
NE FINISHED |
How this triple was built (4 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: Hobbemastraat | Statement: [Museum Square, adjacentTo, Hobbemastraat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hobbemastraat Context triple: [Museum Square, adjacentTo, Hobbemastraat]
-
A.
Hoveniersstraat
Hoveniersstraat is a prominent street in Antwerp, Belgium, renowned as a central hub of the city's diamond trade and industry.
-
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.
Spuistraat
Spuistraat is a central street in Amsterdam known for its historic buildings, shops, and proximity to major city landmarks.
-
D.
Heemstedestraat
Heemstedestraat is a metro station in Amsterdam that serves as a stop on the city’s rapid transit network.
-
E.
Vijzelstraat
Vijzelstraat is a major street in central Amsterdam, Netherlands, running between the city’s historic canals and serving as an important traffic and commercial route.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hobbemastraat Triple: [Museum Square, adjacentTo, Hobbemastraat]
Generated description
Hobbemastraat is a street in Amsterdam, Netherlands, known for its proximity to major museums and cultural attractions near Museumplein.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hobbemastraat Target entity description: Hobbemastraat is a street in Amsterdam, Netherlands, known for its proximity to major museums and cultural attractions near Museumplein.
-
A.
Hoveniersstraat
Hoveniersstraat is a prominent street in Antwerp, Belgium, renowned as a central hub of the city's diamond trade and industry.
-
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.
Spuistraat
Spuistraat is a central street in Amsterdam known for its historic buildings, shops, and proximity to major city landmarks.
-
D.
Heemstedestraat
Heemstedestraat is a metro station in Amsterdam that serves as a stop on the city’s rapid transit network.
-
E.
Vijzelstraat
Vijzelstraat is a major street in central Amsterdam, Netherlands, running between the city’s historic canals and serving as an important traffic and commercial route.
- F. None of above. chosen
Provenance (5 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a76ae688190b068e4c92603a16d |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc936b4d088190bfcfd3bc6c05f7e8 |
completed | April 1, 2026, 3:39 a.m. |
| NEDg | Description generation | batch_69cc955542fc8190a84be60f4efea915 |
completed | April 1, 2026, 3:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc964c6b308190ae121072b1180268 |
completed | April 1, 2026, 3:51 a.m. |
Created at: March 30, 2026, 5:05 p.m.