Triple
T15137295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leipziger Straße intersection |
E361586
|
entity |
| Predicate | crossesStreetWithDirection |
P51219
|
FINISHED |
| Object | north–south |
—
|
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: north–south | Statement: [Leipziger Straße intersection, crossesStreetWithDirection, north–south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesStreetWithDirection Context triple: [Leipziger Straße intersection, crossesStreetWithDirection, north–south]
-
A.
crossesStreet
Indicates that an entity moves from one side of a street to the other, traversing the street’s width.
-
B.
crossingDirection
chosen
Indicates the direction in which one entity moves or passes across another reference point, boundary, or path.
-
C.
crossedByHighway
Indicates that a highway passes across or through the extent of a given entity or area.
-
D.
mainRoadCrossingBetween
Indicates that a primary or main road intersects or passes between two specified locations or entities.
-
E.
directionFromCharingCross
Indicates the compass direction of one place or object as measured from Charing Cross.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b59b488190b0016970647e7483 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.