Triple
T14123939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saarlouis |
E339974
|
entity |
| Predicate | distanceToSaarbrücken |
P112900
|
FINISHED |
| Object | about 20 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: about 20 km | Statement: [Saarlouis, distanceToSaarbrücken, about 20 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSaarbrücken Context triple: [Saarlouis, distanceToSaarbrücken, about 20 km]
-
A.
distanceFromStrasbourg
Indicates the spatial distance between a given place or entity and the city of Strasbourg.
-
B.
distanceToWetzlar
Indicates the measured distance between a given entity or location and the place named Wetzlar.
-
C.
distanceToMetzKilometers
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Metz.
-
D.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
-
E.
distanceToFrankfurt
Indicates the spatial distance between a given location or entity and the city of Frankfurt.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:22 p.m.