Triple
T28631776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boxhagener Platz |
E724657
|
entity |
| Predicate | hasSurroundingStreets |
P87577
|
FINISHED |
| Object | Gabriel-Max-Straße |
—
|
NE NERFINISHED |
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: Gabriel-Max-Straße | Statement: [Boxhagener Platz, hasSurroundingStreets, Gabriel-Max-Straße]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundingStreets Context triple: [Boxhagener Platz, hasSurroundingStreets, Gabriel-Max-Straße]
-
A.
surroundedByStreet
chosen
Indicates that an entity is encircled or enclosed on all sides by one or more streets.
-
B.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
C.
hasNearbyStreetPattern
Indicates that one location has a street layout or configuration that is spatially close to, or in the vicinity of, another location’s street pattern.
-
D.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
-
E.
hasCrossStreets
Indicates that a location is situated at or near the intersection of the specified streets.
- 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_69f01d8328c48190bc0e5f9b9b848582 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 28, 2026, 4:37 a.m.