Triple
T13134827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de la Science / Wetenschapsstraat |
E312054
|
entity |
| Predicate | hasStreetNamingConvention |
P36245
|
FINISHED |
| Object | named after science |
—
|
LITERAL 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: named after science | Statement: [Rue de la Science / Wetenschapsstraat, hasStreetNamingConvention, named after science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetNamingConvention Context triple: [Rue de la Science / Wetenschapsstraat, hasStreetNamingConvention, named after science]
-
A.
hasStreetNamingPattern
chosen
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
B.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
C.
hasStreetNameElement
Indicates that an address or location includes a specific street name component as part of its full designation.
-
D.
hasStreetNickname
Indicates that an entity is known by a particular informal or colloquial name used on the street or in everyday speech.
-
E.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
- F. None of above.
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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b3d72c8190b69ae56435a954fa |
completed | April 10, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69d9804543cc8190a23cd7da59a12a7b |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:08 p.m.