Triple
T35574818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ladenburg station |
E1028045
|
entity |
| Predicate | distanceFromMannheimHbf_km |
P207055
|
FINISHED |
| Object | approximately 11 |
—
|
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 11 | Statement: [Ladenburg station, distanceFromMannheimHbf_km, approximately 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMannheimHbf_km Context triple: [Ladenburg station, distanceFromMannheimHbf_km, approximately 11]
-
A.
distanceFromMainzHbf
Indicates the spatial distance between an entity and Mainz Hauptbahnhof (Mainz central railway station).
-
B.
distanceFromDarmstadtHbf
Indicates the spatial distance between a given location and Darmstadt Hauptbahnhof (Darmstadt central railway station).
-
C.
distanceFromHagenHbf_km
Indicates the distance, measured in kilometers, between a given location and Hagen Hauptbahnhof (Hagen central railway station).
-
D.
distanceToFrankfurtHbf
Indicates the spatial distance between a given location and Frankfurt Hauptbahnhof (Frankfurt Hbf).
-
E.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
- F. None of above. chosen
Provenance (4 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.