Triple
T38236021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Designer Outlet Berlin |
E1013621
|
entity |
| Predicate | distanceFromBerlinCenter |
P3430
|
FINISHED |
| Object | approximately 30 km west |
—
|
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: approximately 30 km west | Statement: [Designer Outlet Berlin, distanceFromBerlinCenter, approximately 30 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBerlinCenter Context triple: [Designer Outlet Berlin, distanceFromBerlinCenter, approximately 30 km west]
-
A.
distanceToBerlin
chosen
Indicates the spatial distance between a given entity’s location and the city of Berlin.
-
B.
distanceFromHagenHbf_km
Indicates the distance, measured in kilometers, between a given location and Hagen Hauptbahnhof (Hagen central railway station).
-
C.
distanceToBonnCentre
Indicates the spatial distance between a given location and the center of Bonn.
-
D.
distanceToFrankfurtHbf
Indicates the spatial distance between a given location and Frankfurt Hauptbahnhof (Frankfurt Hbf).
-
E.
distanceFromDarmstadtHbf
Indicates the spatial distance between a given location and Darmstadt Hauptbahnhof (Darmstadt central railway station).
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.