Triple
T17248585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedberg (Hesse) |
E418690
|
entity |
| Predicate | distanceTo Frankfurt am Main |
P88078
|
FINISHED |
| Object | about 30 kilometres north |
—
|
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: about 30 kilometres north | Statement: [Friedberg (Hesse), distanceTo Frankfurt am Main, about 30 kilometres north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceTo Frankfurt am Main Context triple: [Friedberg (Hesse), distanceTo Frankfurt am Main, about 30 kilometres north]
-
A.
distanceToFrankfurt
chosen
Indicates the spatial distance between a given location or entity and the city of Frankfurt.
-
B.
distanceToFrankfurtHbf
Indicates the spatial distance between a given location and Frankfurt Hauptbahnhof (Frankfurt Hbf).
-
C.
distanceToStuttgart
Indicates the measured distance between a given entity’s location and the city of Stuttgart.
-
D.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
-
E.
distanceToBerlin
Indicates the spatial distance between a given entity’s location and the city of Berlin.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e2569c081908ffd3ee9c76bcc17 |
completed | April 19, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.