Triple
T13134803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de la Science / Wetenschapsstraat |
E312054
|
entity |
| Predicate | languageOfFrenchName |
P15
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Rue de la Science / Wetenschapsstraat, languageOfFrenchName, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFrenchName Context triple: [Rue de la Science / Wetenschapsstraat, languageOfFrenchName, French]
-
A.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
B.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
C.
languageOfNamesake
Indicates the language in which the namesake of an entity (such as a person, place, or object) is named or expressed.
-
D.
languageFamilyOf
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
E.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
- 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.