Triple
T30650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auschwitz-Birkenau |
E610
|
entity |
| Predicate | railConnection |
P848
|
FINISHED |
| Object | connected to major European ghettos and cities |
—
|
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: connected to major European ghettos and cities | Statement: [Auschwitz-Birkenau, railConnection, connected to major European ghettos and cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railConnection Context triple: [Auschwitz-Birkenau, railConnection, connected to major European ghettos and cities]
-
A.
railwayLine
chosen
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
D.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490d80a0819083bf604c1229e903 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486eb01881909241540dda28e1ff |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.