Triple
T32534116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palatinate Ludwig Railway (Ludwigshafen–Saarbrücken line) |
E831542
|
entity |
| Predicate | connectsToRiver |
P180780
|
FINISHED |
| Object | Rhine |
—
|
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: Rhine | Statement: [Palatinate Ludwig Railway (Ludwigshafen–Saarbrücken line), connectsToRiver, Rhine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToRiver Context triple: [Palatinate Ludwig Railway (Ludwigshafen–Saarbrücken line), connectsToRiver, Rhine]
-
A.
linkedToRiver
chosen
Indicates a relationship where something is physically or functionally connected to, associated with, or dependent on a river.
-
B.
connectsToRiverPort
Indicates that one location, route, or infrastructure element has a direct linkage or access to a river port.
-
C.
locatedInRiverArea
Indicates that one entity is situated within the geographic area occupied by, adjacent to, or directly associated with a particular river.
-
D.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
E.
joinsRiverNear
Indicates that one river or watercourse flows into and merges with another river at or close to a specified location.
- 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: May 1, 2026, 1:01 a.m.