Triple
T36995745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sieg |
E915222
|
entity |
| Predicate | hasRailwayValleyLine |
P55241
|
FINISHED |
| Object | Sieg Railway |
—
|
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: Sieg Railway | Statement: [Sieg, hasRailwayValleyLine, Sieg Railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailwayValleyLine Context triple: [Sieg, hasRailwayValleyLine, Sieg Railway]
-
A.
hasValleyRailLine
chosen
Indicates that a location or region is traversed or served by a railway line running through a valley.
-
B.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
C.
hasValleyAccessTo
Indicates that one location can be reached from another specifically by traveling through a valley or valley-based route.
-
D.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
-
E.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fdd2be648c8190b60b3d1caeb44364 |
completed | May 8, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69fdd14a5c708190a6f95ec61f4fc28f |
completed | May 8, 2026, 12:04 p.m. |
Created at: May 3, 2026, 4:14 p.m.