Triple
T2060402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museumsufer Frankfurt |
E45774
|
entity |
| Predicate | hasBicyclePath |
P1709
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Museumsufer Frankfurt, hasBicyclePath, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBicyclePath Context triple: [Museumsufer Frankfurt, hasBicyclePath, yes]
-
A.
hasBicycleFacilities
chosen
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
-
B.
bicycleUse
Indicates that an entity makes use of a bicycle for transportation, activity, or other purposes.
-
C.
hasRideCycle
Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
-
D.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
E.
hasWheelchairLanes
Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9cfdac88190b8b7af1bfea6a78e |
completed | March 7, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69abb7ad5a7c8190b92575d6053b3fb7 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:40 p.m.