Triple
T27997934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langen (Hess) station |
E707065
|
entity |
| Predicate | distanceFromDarmstadtHbf |
P200750
|
FINISHED |
| Object | approximately 18 km |
—
|
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 18 km | Statement: [Langen (Hess) station, distanceFromDarmstadtHbf, approximately 18 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDarmstadtHbf Context triple: [Langen (Hess) station, distanceFromDarmstadtHbf, approximately 18 km]
-
A.
distanceToFrankfurtHbf
Indicates the spatial distance between a given location and Frankfurt Hauptbahnhof (Frankfurt Hbf).
-
B.
distanceFromHagenHbf_km
Indicates the distance, measured in kilometers, between a given location and Hagen Hauptbahnhof (Hagen central railway station).
-
C.
distanceFromMainzHbf
Indicates the spatial distance between an entity and Mainz Hauptbahnhof (Mainz central railway station).
-
D.
distanceToWuppertal
Indicates the spatial distance between a given entity and the location of Wuppertal.
-
E.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
- 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ffab5adf2c819084700c5ea34615bf |
completed | May 9, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69ffaabffa208190b5214ca17cc8a5ea |
completed | May 9, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69ffab59fe408190b72f13016de9953c |
completed | May 9, 2026, 9:47 p.m. |
Created at: April 27, 2026, 7:54 p.m.