Triple
T13134944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de Spa / Spaansestraat |
E312058
|
entity |
| Predicate | hasNameInDutch |
P13254
|
FINISHED |
| Object |
Spaansestraat
Spaansestraat is the Dutch name for Rue de Spa, a street in Brussels, Belgium.
|
E1047554
|
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: Spaansestraat | Statement: [Rue de Spa / Spaansestraat, hasNameInDutch, Spaansestraat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spaansestraat Context triple: [Rue de Spa / Spaansestraat, hasNameInDutch, Spaansestraat]
-
A.
Schupstraat
Schupstraat is a prominent street in Antwerp’s Diamond District, known for its dense concentration of diamond shops and related businesses.
-
B.
Spuistraat
Spuistraat is a central street in Amsterdam known for its historic buildings, shops, and proximity to major city landmarks.
-
C.
Stoofstraat
Stoofstraat is a small, historic street in central Brussels, Belgium, located near the famous Manneken Pis statue.
-
D.
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.
-
E.
Zadelstraat
Zadelstraat is a historic shopping street in the center of Utrecht, Netherlands, known for its old buildings, boutiques, and cafés leading toward the Dom Tower.
- 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: Spaansestraat Triple: [Rue de Spa / Spaansestraat, hasNameInDutch, Spaansestraat]
Generated description
Spaansestraat is the Dutch name for Rue de Spa, a street in Brussels, Belgium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Spaansestraat Target entity description: Spaansestraat is the Dutch name for Rue de Spa, a street in Brussels, Belgium.
-
A.
Schupstraat
Schupstraat is a prominent street in Antwerp’s Diamond District, known for its dense concentration of diamond shops and related businesses.
-
B.
Spuistraat
Spuistraat is a central street in Amsterdam known for its historic buildings, shops, and proximity to major city landmarks.
-
C.
Stoofstraat
Stoofstraat is a small, historic street in central Brussels, Belgium, located near the famous Manneken Pis statue.
-
D.
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.
-
E.
Zadelstraat
Zadelstraat is a historic shopping street in the center of Utrecht, Netherlands, known for its old buildings, boutiques, and cafés leading toward the Dom Tower.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b3d72c8190b69ae56435a954fa |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d7cfe24819096e8f4cd496a6fd7 |
completed | May 3, 2026, 2:36 p.m. |
| NEDg | Description generation | batch_69f7614fbe8c8190b4a32b129c64d6b0 |
completed | May 3, 2026, 2:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f761a9e7448190835cfff6a1ad6405 |
completed | May 3, 2026, 2:54 p.m. |
Created at: April 9, 2026, 9:08 p.m.